improved efficiency

7 Invaluable Benefits of Data-Driven Decision making

7 Invaluable Benefits of Data-Driven Decision- making

The benefits of data-driven decision-making are there, as long as you put in the work to find the value and take action. Analytics pays back $13.01 for every $1 spent. That’s a 1,201% ROI. I don’t know about you, but 1200%+ ROI sounds pretty good to me. That’s a number that I would definitely feel good about.

Data is an invaluable piece of your manufacturing company when utilized correctly. I can’t stress enough how important it is and continues to become for manufacturing companies to adapt to the changes in the industrial landscape and strive to become data-driven organizations.

As funny as it is to say, the data backs it up. Data says that becoming data-driven is extremely beneficial for any company, especially manufacturers. In manufacturing, there is just so much information left on the table. There are so many moving parts and people at any given time. With that amount of constant movement between all of the machines, people, products, materials, and equipment; there is inevitably an enormous amount of waste, whether that waste is physical scrap or simply wasted movement. There is always a lot of room for improvement, and it starts with tracking these metrics and processes.

We believe the benefits of data-driven decision-making are extremely valuable, and data-driven manufacturing should not be viewed as just a “nice extra” for the companies that want to do more today. We believe that adopting data-driven tendencies will be required in the not-so-distant future for any company that wants to grow and succeed. Let’s get into some specific benefits that come along with data-driven decision-making.

1. Ability to Develop a Competitive Advantage

Illustration showing how the benefits of data driven decision making can give you a competitive advantage.

Competition in every industry continues to increase every year, every month, every day. Companies are constantly struggling to keep up and find ways to get ahead of the curve. However, there are of course numerous ways for companies to compete and succeed. One way to succeed today is to create data asymmetry in your market. Data asymmetry allows you to ask questions and get answers that the competition can’t. Well-known successful Companies like Google, Uber, Facebook, and Airbnb use data asymmetry to develop a unique competitive advantage- you can do the same.

2. Confident Business Decisions

confident vs confused

Data gives you the substance to make confident decisions on a consistent basis. A confident decision leads to real action, not just a conversation that never gets anywhere because of some uncertainty. You need to have full confidence in the decisions you make to carry them out. With that being said, the real value comes when you enable yourself to take action.

3. Data Enables Action

take action

Companies will succeed not only due to their competitive advantage that is driven by data. They’re also winning because they’re able to “USE the data most effectively”. Making good decisions comes from:

  • Having a good process for solving problems, and
  • Having data and related tools to find answers and solve those problems.

Once the decision is made then it’s time for Action. Nothing happens without taking action.

4. Improved Plant-Floor Efficiency

improved efficiency

What gets tracked gets improved. 

If you could track and gather insights on downtime, downtime reason codes, which operator was running the machine at what time, how long the shift was, what product was being run, scrap, throughput, operator changeovers, product changeovers, would that information be useful? Of course it would!

Without the data, you would be going in blind. Or at best, basing your decisions on a gut feeling or past experiences. This might have been a viable approach some years ago, but today in 2021 there are too many resources available that are much better options. If you don’t take advantage, somebody else will, and whoever does will be the one who continues to grow and find success in this competitive industry today. There is ALWAYS someone trying to do your job better, faster, cheaper, and willing to put in the effort to get there.

5. Cost Savings

cost savings

Cost savings go hand in hand with improving efficiency. Improved efficiency means less waste and consequently, less cost. You will really start to see a difference when you improve inefficient processes to take less time and start capturing insights on scrap and downtime to reduce waste. Use data to combine reducing costs + improving efficiency to get more done in less time, with what you already have. Eliminate and reduce unnecessary movement and scrap by implementing data-driven decision-making.

6. Company Culture

Establish a data-driven company culture to reap the benefits of data driven decision making.

Along with implementing data-driven decision-making, you need to establish a unified data-driven culture. For more in-depth information on the journey to creating a data-driven culture, check out this blog post. The post touches on the 5 facets of a data-driven organization as well the 4 stages most companies go through on their way to becoming a truly data-driven organization.

Establishing a data-driven culture can make a huge impact. Employees will be more involved, be enabled to be proactive, have access to the same information as everyone else, and everyone will be on the same page.

Having access to the same data acts as a communication tool in a way. Good communication is an important aspect of any relationship – whether it’s work-related or not; good communication keeps people happier, creates less confusion, and promotes an efficient environment.

This helps create a real team within the company, rather than sectioned off people or departments with their own silos of data doing their own thing. More often than not, those data silos and cliques within the organization end up hindering other departments. Each separate department should act as a service organization for the others, rather than a roadblock in the way making things harder than they have to be.

7. Improved Capacity to Scale and Grow

Gaining the ability to grow and scale the company is one of the major benefits of data driven decision making.

Numerous studies show that simply setting goals makes people much more productive, and people that plan better and stick to goals end up reaching those goals much more often.

Being data-driven and equipping yourself with the right tools and technologies grants you access to the metrics you need to be able to set goals and measure results. Set goals, stick to them, and work towards them each day. Data makes it much easier to make seemingly small, incremental adjustments continuously. This creates opportunities to execute new ideas, measure results, and either keep the course or change plans very quickly. Real-time data makes organizations much more agile and open to growth.

Final thoughts on Data-Driven Decision-Making

Starting a data-driven approach does not all need to take place all at once or be a complete overnight flip. It surely doesn’t mean that you should start to completely dismiss intuition and opinions. Although becoming data-driven is extremely important, we don’t want to give off the impression that past experience and common sense are “outdated” or have no place in the modern workplace.

Transitioning into a data-driven organization means that data should drive the majority of the workflow. Leadership should make data-driven decisions and carry them throughout the entire company. When this happens, everyone benefits.

Also, don’t forget that a data-driven approach is not only for the top 1% of companies and massive corporations. Any sized company can start today and begin the journey towards becoming a completely data-driven organization and reap the benefits.

Starting now, and being ahead of the curve will be greatly beneficial for increasing efficiency and improving company agility.

Start small, think big.

Use this simple formula for lead time improvement

Simple Formula for Lead Time Improvement

Simple Formula for Lead Time Improvement

Lead time improvement for manufacturers will always be an issue. Simply because any manufacturing process will never be completely optimal, there is always going to be room for improvement. That is the mindset manufacturers must have in order to grow and remain successful.

On-time delivery and lead time improvement are complex issues because there are so many factors, everything is involved. The back office is involved, suppliers are involved, everyone and everything on the plant floor is involved. When you try to focus on improving lead times and OTD, you can get overwhelmed very quickly. Where do you start? Why? What will actually help? How do you know if the adjustment you made even made a positive impact or not?

Small, Incremental Changes

Small, incremental changes are the key to improving lead times. With a process so complex, you need to tackle it one step at a time. You aren’t going to be able to change everything at once, it won’t happen overnight. Furthermore, if you make too many changes at one time, how do you gauge what worked and what didn’t? It’s almost impossible to make that differentiation.

What do you need to help you get there? We’ve established that making small incremental changes is a viable approach, but there are still so many areas to improve. How do you decide where to start?

It’s like walking up a staircase. Each step is small, but after a little bit, once you get to the top and look at how far you’ve gone, you realize how each small step added up to make a big impact. Furthermore, you made it easy by taking it one step at a time, small incremental progress. Think about how much tougher it would have been if all you saw was where you stand, and where you need to end up, 50 feet higher. Don’t make it harder than it has to be!

Graphic showing how small incremental changes are the best approach for lead time improvement.

Equip Yourself with the Proper Tools

Managing the entire manufacturing process from beginning to end is no small task. That’s where modern manufacturing intelligence solutions, such as an MES, can step in. An MES can manage everything that happens on the plant floor- every person, every machine, every product, and every process. In order to start making changes, you need information. You need to know what is happening on the plant floor- when materials arrive, who is running what machine, how much downtime you encountered, how much scrap, how long do your changeovers take, and the list goes on.

If you don’t know any of these things, how will they get improved? How would you cut back on downtime if you don’t know what’s causing it? Or, how do you improve changeover times if you don’t know how long your current changeovers are?

On the flip side, if you have access to this information, you can start making decisions based on it. Decide on a few metrics to track in areas that you can improve, gather the data, analyze it, and make a data-driven decision.

Data drives our world, and it should be driving the changes you make on the plant floor to improve lead times and your overall manufacturing process. However, this is only the first step. Nothing happens until you take action.

Enable Yourself to Take Action

Once you are equipped- you have the tools you need, you’re tracking metrics and processes, and you’re making data-driven decisions to improve your process. Now, it’s time to take action. Nothing happens until you take action. Time to execute.

It almost sounds too simple. Not easy, but simple. The whole process is to gather information, make a decision, and take action. Make the data work for you, leverage it, use it to your advantage.

Example

The process could look something like this for example: Let’s say that you are a discrete manufacturer, and you determined that with the numerous product changeovers that take place every day, that would be a good process to start tracking and drive improvement.

You start gathering data and notice that operator 1 is much more efficient than operator 2. So, you start to analyze the data and find out why. Once you come to a conclusion based on the data, drive action. Maybe it was operator 1’s loading tendencies that made his product changeovers so much more efficient. Take note of that, and make it part of the standard process among the entire company.

Boom! One thing off the list- product changeovers are improved, you can use real-time data to instantly gauge results, and move on to the next area.

That’s one more small, incremental step towards an extremely efficient manufacturing process and improved lead times.

Concluding Thoughts on Lead Time Improvement

Now, will this cut your lead times in half overnight? No, but the sequences of small incremental changes make a big difference over time. Make sure that you are 1. Equipped, and 2. Enabled. This way, you will know:

  • Where you stand,
  • How to identify your own inefficiencies,
  • Where you can improve, and
  • How much of an impact your adjustments really made.

We all want results instantly, but oftentimes that is not reality. Position yourself to make quick wins on a consistent basis, and continually improve. Establishing these things will put you in a great position for company growth and improvement in many areas, not just in improving lead times.

The little things add up, small but consistent steps will make a big change over time. Remember to make your data work for you, take it one step at a time, and be proactive.

This graphic shows the different sources of data and information that can come together to make strong contextual data.

Why Contextual Data on the Plant Floor is a Must-Have.

Why Contextual Data is a Necessity for the Plant Floor of the Future

Yes, Contextual data is a requirement for the plant floor of the future, most definitely not just the icing on the cake. Further on that point, we may be talking about the not-so-distant future. Or even right now, today.

Before we get into it, here is the definition of contextual data: information or a set of circumstances that form the setting for an event or idea for a thing in terms that it can be fully understood and assessed.

Throughout the remaining parts of this article, I will explain to you why contextual data is absolutely a requirement. Also, why you should get started now before you get left behind.

The State of the Manufacturing Industry Today

The majority of manufacturers today are aware that we are exiting the 3rd industrial revolution, and Industry 4.0 is making its grand entrance. Let’s quickly recap why this is so important that I felt it was necessary to make this the first major point in this article.

Industry 3.0

Machine automation. Cool, right? Yes, machine automation has been huge for the manufacturing industry and is of course still extremely relevant and valuable today. However, there’s another level to it now, now we can automate much more than just machines on the plant floor.

Industry 4.0

Business process automation. This is the next step. Industry 4.0 does not completely reinvent the modern-day physical factory. Factories actually look extremely similar to Industry 3.0. What it does do, is reinvent the way we approach processes and unlocks the “hidden factory.” The hidden factory is all of the data and information that has been trapped inside of machines from Industry 3.0 that simply could not be extracted or used before. Industry 4.0 ties the whole company together to, once again, automate business processes. You have the back office, the plant floor, and everything in between- Industry 4.0 brings the capability to fluently make these departments or sections of the company work together for better business.

Don’t forget Your other Half

The back office portion of manufacturing companies has already been revolutionized Industry 4.0 style with ERP systems. One problem is that many people believe that ERP systems can act as an MES or IIoT system. ERP systems aren’t built for this, and they are simply incapable. ERP systems are for the back office, they do a great job at what they do, but that job does not take place on the plant floor.

You need contextual data in the back office and the plant floor.

What you need, is the plant floor version of an ERP- a system that can collect and analyze data + communicate effectively with other systems (such as your ERP system). This is called an MES (manufacturing execution system). ERP systems came along and they made a huge impact, they’re standard today. Now, MES is next. MES bridges the gap between the back office and the plant floor.

Why is this Important?

MES and IIoT (Industrial Internet of Things) systems provide contextual data from the plant floor. These systems complete the circle that allows each section of the company to gather, analyze, and share contextual data to automate business decisions. Contextual data drives business decisions. This is what Industry 4.0 is all about, and this is the (not so distant) future of manufacturing.

Enough explaining why this information is so important to manufacturing companies- Let’s get into the how, and some examples.

Machine Data + Contextual Data

Machine data on its own is okay. Getting dates and times detailing when a machine was down is helpful information. What if you knew why the machine was down, what caused the downtime, the symptoms, and reason codes. Would this information be helpful? Would it assist you in making a decision to improve productivity and your process? Absolutely!

Combine machine data + contextual data to vastly improve production on the plant floor.

Having basic data to analyze the most common causes for downtime code by occurrence and duration goes a long way in helping you solve downtime issues for your machine. But think about all of the other data in your company and the data surrounding that machine. Name of the operator, job or part being run on the machine, the shift, the level of training of that operator, and a host of other data points. When looking at the downtime of the machine would it be helpful to not only know why the machine was down but also what part was being produced, who the operator was, etc? Again, of course!

How You Can Gain Access to Contextual Data

So, how do we connect the contextual data with the machine data to get extreme value? Answer: Through thoughtful planning, an open mind to new ideas, use of best practices, and open nonproprietary technology.

As an example, we have two different approaches to this challenge. The first is to use a product like-

SensrTrx:

SensrTrx is a single system into which a lot of machine and contextual data can easily be combined, analyzed, and displayed.

For More Complex and Challenging Scenarios:

We implement architectures that use MQTT data brokers, the unified namespace, and open technology tools. The data broker and a unified namespace are two key pieces of the puzzle that enable us to combine the machine data with many layers of contextual data from the rest of the plant. We have multiple videos on our YouTube channel which describe how these architectures work and how quickly they can be put in place.

Don’t be part of the 92%

11 out of 12 companies fail industrial transitions and end up either 1. Going out of business or  2. Getting bought out. Historically, this has happened throughout the first 3 industrial revolutions. Now, as the 4th industrial revolution has begun, it’s important to be adaptable. Adjust to the changes in the manufacturing landscape, and fall in line with that 8% of companies that successfully make the transition.

In order to remain competitive and stay in business today, you need to take the next step, create a data-driven company culture, and be proactive.

If you have any questions at all, don’t hesitate to leave us a message here. We have decades of experience in the industry and we could talk about data-driven manufacturing, contextual data, Industry 4.0, and similar topics all day long.

This image show the impact that your lean efforts can have on profit margins and waste in the factory.

How to Supercharge Your Lean Efforts in 2021

How to Supercharge Your Lean Efforts

Modern technology has created new ways that assist you in maximizing the results from your lean efforts. Back in the mid-1900s, Toyota invented the Toyota Production System (TPS). This process emphasized a set of manufacturing principles that are still very relevant today. Now, this process is more commonly referred to simply as lean manufacturing. Although the principles haven’t changed over time, the way that we follow them has. Thanks to modern technology, you can supercharge your lean efforts and see results much faster than before.

Why Lean Manufacturing is About Subtraction, Not Addition

Lean manufacturing is not about adding any more machines or more people to the plant floor. It takes a different approach to improve processes and gain more production in the same amount of time. It’s really all about subtraction, it’s about elimination.

Eliminate scrap, eliminate waste, eliminate excess inventory, and eliminate nonvalue-adding movement. Lean manufacturing is centered around improving and perfecting your current process. You would be hard-pressed to find an industry with more movement than manufacturing. Tons of operators and employees working on the plant floor at any given time, numerous machines and equipment spread all across the plant floor that needs to be producing constantly.

The large volume of people and equipment makes all wasted movement and material add up extremely quickly. It gets expensive fast and eats into companies’ profits. That’s why lean manufacturing is so very important. At Ectobox, we like to say- “Learn how to do more with what you already have.” By implementing lean practices throughout your processes, you can do exactly that.

5 Steps to Successful Lean Manufacturing

In order to do more with what you already have, you will need to follow these 5 steps.

  1. Define Value 
  2. Map the Value Stream 
  3. Create Flow
  4. Establish Pull 
  5. Pursue Perfection

 

  1. Define Value

    Value is whatever someone is willing to pay for something. Take the time to discover what your customers actually need and want. Sometimes customers won’t know exactly what they need, then it becomes your job to find out. Once you do find out, you can then determine what they want, how much, when, and what fits their price range.

  2. Map the Value Stream

    Once you have defined value, use that as your reference point. The next step is to review and diagram the flow of product through your plant and document the processes (manual and automated) that are executed. Then, evaluate them- determine if each activity is adding to your defined value or not. If an activity is not adding value, that activity is considered waste. You can separate these activities into nonvalue-add but necessary, and nonvalue-add and unnecessary. The unnecessary activities should be completely eliminated, the nonvalue-add but necessary activities should be reduced as much as possible.

  3. Create Flow

    Avoid delays and interruptions. Make sure your employees are skilled and adaptive, break down each step, and ensure that everyone is on the same page. In doing so, you can keep production smooth and consistent.

  4. Establish Pull

    One of the biggest wastes in any production system is inventory. A pull-based system is meant to limit inventory as much as possible while ensuring that the materials needed are available right at the time you need them. This in effect, limits waste while also keeping a smooth workflow.

  5. Pursue Perfection

    Make Lean thinking and continuous improvement a part of your company culture. Strive for perfection, and don’t stop until you get there. Be proactive about developing a better organization and constantly find ways to improve efficiency.

The Key to Supercharging Your Lean Efforts Today

The key to supercharging your lean efforts is to take advantage of modern manufacturing intelligence systems. Remember that lean isn’t about adding, it’s about current process improvement. What’s the first step here? How do you get started? By tracking those processes. Tracking manufacturing processes in the most efficient, credible, and detailed way is the first step to getting the most out of your lean efforts.

How Industry 4.0 makes Lean Manufacturing Twice as Valuable

Gone are the days of manually recording data, or at least they should be.

The Toyota production process was invented during Industry 2.0- the revolution that brought assembly lines and mass production. Then soon after, we saw Industry 3.0- computerized and automated machines. Today, we are in Industry 4.0- data and the automation of business processes.

Physically, factories look generally the same as they did in Industry 3.0. The key difference is data. Modern Industry 4.0 systems grant manufacturers the ability to gather, contextualize, and analyze data that was never attainable before. We sometimes like to refer to this as “the hidden factory.”

When you think about it, lean is not really about manufacturing itself. Lean is about the business decisions made that improve the efficiency of a manufacturing process.

Combining lean thinking with Industry 4.0 technology, and utilizing both to drive better decision-making is a recipe for success.

Unlock the Hidden Factory

Unlock the hidden factory with a modern manufacturing intelligence solution such as an IIoT or MES system for the plant floor. Gain insights on downtime, product changeovers, operator changeovers, production schedules, scrap, and much more. Unlock the ability to track every person, every movement, process, and machine within the 4 walls of the plant floor. Use real-time data to make quick decisions that reduce waste and improve process efficiency.

Systems with these capabilities expedite lean manufacturing practices and take them to another level.

The Ultimate Manufacturing Tag-Team

Lean practices + modern manufacturing intelligence solutions = the ultimate manufacturing tag team.

When you combine following the principles and ideas that promote reducing waste, adding value, and creating the most efficient environment possible with a system that provides you with deep, detailed, accurate sets of real-time data to quickly make decisions and adjustments- you’re putting yourself in a great spot. Positioning yourself for company growth and success now and in the future.

Lean Manufacturing Boot Camp

Presented by SPEDE Manufacturing 

Wed, Oct 20, 2021, 8:00 AM –Thu, Oct 21, 2021, 4:00 PM EDT

An intensive 2-day boot camp designed to help you learn the tools you need to implement Lean Manufacturing and how these tools can be used to help your business succeed.

Get Tickets Here!

Illustration showing two cars, one with many "micro stops" holding it back, and the other with only a couple stops- allowing the second car to reach the destination much quicker.

Are Micro Stops Quietly Gashing Your Production Efficiency?

Are Micro Stops Quietly Gashing Your Production Efficiency?

Micro stop: When a machine or piece of equipment quickly stops and resumes production, typically as a result of a temporary issue that is resolved in just a few seconds or minutes.

These small, quick micro stops may seem harmless and just a part of the process. While it’s near impossible to completely eliminate all micro stops on the plant floor, they can actually make a huge impact on your overall production efficiency and your bottom line.

Although downtime is a popular topic, capturing downtime occurrences, reasons, and developing a deeper understanding of what is really happening on the plant floor has proven to be a struggle for the majority of manufacturers.

If manufacturers are unwilling or not properly equipped to capture downtime reason codes from complete machine failures, you can only imagine how many micro stoppages are being completely ignored on a daily basis.

These micro stops are eating into your production efficiency, yet it seems to be the downtime that no one pays any attention to.

The Downtime that Nobody Talks About

As I mentioned, everyone talks about downtime, but not this kind, not micro stops.

It’s fair to say that you want to tackle the biggest problem first. You want to spend your time, energy, and resources solving the most important, most valuable problems. With that being said, how do you really know what your biggest problem or biggest inefficiency is? You might be surprised if you saw some numbers rather than relying on a gut feeling or reasoning that x is just obviously more important compared to other issues.

For many manufacturers, especially discrete manufacturers- micro stoppages end up accounting for more downtime than “big” downtime. The high volume of product changeovers and movement around the plant floor makes the numbers add up quickly.

The problem is that manufacturers A) are not tracking processes, and B) constantly overlook and completely ignore micro stops. If a machine fails and is down for a couple of days, you would of course realize it, and ensure that the issue is resolved and the machine is up and running again as soon as possible. On the other hand, when a machine stops production for 30 seconds here and a couple of minutes there due to a small temporary issue, you very likely just fix it and keep going. The odds are, you never think about the issue again and just keep moving.

These micro stops occur many, many times throughout the day. I’m not saying that you should spend 20 minutes analyzing a 30-second problem all day long. However, I am saying that gathering information and making the proper adjustments to increase throughput and machine utilization in the long term is unquestionably worth it.

What Counts as a Micro Stop?

Micro stops can account for a large portion of overall downtime and have a major impact on your OEE. Micro Stops can really be anything that causes downtime for a short period of time. Here are some common reasons for Micro Stops:

  • Operator error
  • Small machine configuration errors
  • Machine process parameters
  • Inefficient process loading/unloading parts

Why Manufacturers Struggle to Reduce Micro Stops

It’s actually a really simple answer. Nobody notices micro stops, nobody pays them any attention, so nobody tracks them. How do you expect to improve a process that you know nothing about and that you ignore? Simple answer again – you don’t. However, that is the bigger problem.

The fact that the majority of manufacturers don’t pay attention to micro stops and don’t see a real reason to, shows how much of a non-issue they view it to be. In reality, micro stops have the potential to be your leading cause of downtime or the biggest area for improvement. Manufacturers should strive to have a continuous improvement mindset, which does not mean to only give attention when something is broken. You should be proactively looking for inefficiencies, quickly making adjustments, and keep moving.

What You Can Do

One simple way to cut back on micro stops is by analyzing your top-performing employees. Gather basic data detailing when their machines were producing and not producing, gather time-stamped basic information, track their habits, how they approach situations, their whole process from start to finish.

Then, you analyze that data and make it part of the training. This process works particularly well for machine setups and dealing with product changeovers- times when micro stops occur very often.

Here is how tracking this type of process could work + making a data-driven decision to improve the process:

  1. Pick out a top-performing employee
  2. Track their entire manufacturing process from machine setup to finished product
  3. Gather basic time-stamped data detailing when the machine was producing and not producing
  4. Analyze the data to determine why this employee has fewer downtime occurrences, and what makes their process superior to others
  5. Make this process part of the training for other employees

Simple, but extremely effective. Use your best employees’ experience and good habits to your advantage. We have another article dedicated to detailing this process further and points out how you can create value by taking one of your top employees and “cloning” your other employees to match their tendencies. Click here to check it out.

Track Processes

Manufacturers need to start tracking these processes. Track changeovers, how machines are loaded, which operators have more micro stops than others- and analyze the data to figure out why. Maybe scrap and machine jamming is causing a high volume of micro stops that go unnoticed. Maybe operator changeover times are inefficient. You won’t really know until you start gathering data.

Get Visibility

Machines are only becoming more complex, and harder to understand thoroughly. It’s important to get visibility into your machines, help operators better understand what is actually happening on the inside of them. This will help them to learn what they can do better, why certain problems occur, why the machines are jamming, why so many micro stoppages are continually pausing production, and what specifically is causing downtime.

This data is just sitting trapped inside machines on the plant floor. All you need to do is equip yourself with the right tools to get that data out.

Once you have the data, you can analyze it to find inefficiencies, make quick adjustments, and improve your manufacturing process.

 

Don’t Forget About the Little Things

We’ve all heard somebody say that the little things add up. Whether you’re talking about spending a few dollars here and there or something else, it adds up. We all know it’s true and have seen little things add up to a large sum in one way or another. So, don’t forget about the little things, they make a huge impact. Don’t ignore and dismiss micro stops as just a part of the process or a small hiccup to take care of and forget about.

Processes that are tracked get improved. On the other hand, if you have no information, you have no substance to base a decision on or make any real improvement. Start tracking, start simple, prove the value to yourself and go from there.

Worker confused on what decision to make because of poor data reliability.

Data Reliability: Do you Trust Your Data?

Data Reliability: Do you Trust Your Data?

First of all, if you are even gathering and analyzing data at all, that’s a great start. It encourages the right mindset and means that you are trying to improve your manufacturing process. On the other hand, if you don’t trust your data and have weak data reliability, that data becomes completely useless.

  • Are you hesitant to act on your data?
  • Do you frequently want to rerun the numbers to make sure everything was correct?
  • Do you question the credibility of your data, and seek information from other sources?

If you answered yes to any of those questions, you need to take a step back and reevaluate your options. Data that can’t be trusted is a huge issue, and it becomes a large waste of time among other things.

Data Does Not Help You

(On its own)

If you find that you are hesitant to use your data, hesitant to make any decisions based on your data, and hesitant to act on your data, then what’s the point of acquiring it? Spoiler alert- there really isn’t one. At this point, you are basically just gathering data and information for the sake of gathering it. Not only does this not help you, but it is also setting you back in other areas. You are wasting time, money, resources, and losing production by gathering and analyzing data that you won’t use.

This is why data reliability is so important. Without reliable data, your time and monetary investment get thrown out the window.

What Now?

If you see yourself in a situation similar to this, what do you do? Do you just have to learn to trust your data? Of course not. If you currently don’t trust your data, there’s likely a good reason for that. Maybe you have proven the data to be wrong in the past, maybe you know that it is not being gathered from a reliable source. It could simply be the fact that the data is reliant on humans recording it. We are all well aware that humans make mistakes, and in this case, it causes inaccuracy in the data. Even if a human recording data is “usually’ spot on, what happens when you see a surprising number? Would you trust it enough to act on it, or question it and blame the person who recorded it?

You need to have complete confidence in the data if you are going to actually take advantage of it. You need to get yourself into a system that you can trust. A solution that delivers high-quality and accurate data that is efficient, does not rely on humans recording information, and comes from a very reliable source. Don’t waste your time and energy with a solution that you don’t trust.

Good Data Reliability = Confident Decisions that Drive Action

Even if you “kinda” trust your data, do you trust it enough to make a confident decision and take action? To invest more time, effort, money, and resources into fixing the inefficiency you found? The answer is likely no, or a hesitant maybe. It’s tough to say yes, you can’t be all-in if you are unsure of the credibility.

Illustration of a confident employee because of strong data reliability, information that he can trust and act on.

That is why it’s so important to have a reliable system for gathering and analyzing data. Good data reliability translates to a confident decision. Furthermore, when it comes to acting on your decisions, it’s much easier to act on a decision that you are 100% confident in.

As I mentioned previously, data alone does not help you, simply looking at a set of numbers will not get you anywhere. Making decisions and turning those decisions into action is what will drive improvement. Equip yourself with the right tools to help you solve real challenges.

Improve Efficiency with Good Data Reliability

Solutions with strong data reliability allow you to tackle a problem or inefficiency and move right on to the next. Modern plant floor solutions such as an MES or IIoT solution deliver real-time data to decision-makers constantly. This means you can find an inefficiency quickly, make an adjustment, and again quickly gauge whether that adjustment made a positive impact or not.

This gives employees and operators a lot of clarity. No lingering thoughts in your head wondering if you made the right decision or not based on weak or incomplete data.

Weak data and a lack of data continues to be a huge problem among manufacturing companies. A recent study concluded that 4 out of 5 manufacturers are completely unaware of their own downtime. They have no idea where it’s coming from. You can easily attribute this to simply not having the proper data or systems in place.

Further on that point, downtime get’s extremely expensive. In some industries within the manufacturing sector, the cost of downtime gets up to over $250,000 per hour. That’s a lot of money being thrown away. To each their own, but to me, I’d say that’s a problem worth looking into, and it all starts with gathering data.

This further stresses the importance of having good and reliable data that you can trust. Invest in a solution that provides you with credible information, and the results will quickly prove the value.

Graph illustrating manufacturing efficiency improving.

2 Strikingly Easy Steps to Improve Manufacturing Efficiency

2 Strikingly Easy Steps to Improve Manufacturing Efficiency

Improving manufacturing efficiency doesn’t have to be a super complex process that takes 6 months to get started. Before I give you the wrong idea, I have to say that at Ectobox, we put a massive emphasis on strategic planning. We believe that developing a strong company strategy and thorough planning is far more important than any physical solution or technology put in place. Now that that’s out of the way, we can get on with our main topic for today.

My point is, data comes from many different sources, different solutions, and can be gathered and analyzed in many different ways with each technique having its own pros and cons. Today, we are going to talk about a simple 2 step solution that depending on how you choose to approach it, could be planned out and started within a day.

There are 2 major steps to improving machine setups:
  • Gather and visualize data from the machine during the setups;
  • Review the data with the operator to get insights into what they’re doing.

Simple right? Almost too simple, let me explain more about how one might go about executing these 2 steps.

Every machine shop and precision metals manufacturer is always looking for ways to increase production, reduce scrap, and overall improve manufacturing efficiency (or at least they should be). As a discrete manufacturer with a large number of product changeovers- one area that can always use some attention is the setup of machines. Setups are among the most difficult work one can do in a machine shop.

The Impact Machine Setups have on Overall Manufacturing Efficiency

Improving machine setup procedures increases quality and production on each job. Many shops will have only a few operators that are exceptionally good at the setup work. These few operators prove how efficient machine setup can be. You need to capture and take advantage of their process and experience.

Many times, we see that these operators are asked to handle all of the setups.

Instead of just accepting that one person knows how to tackle a certain situation better than another, why not find out why and use it as training for the other willing and capable operators? If one person can accomplish a process effectively, so can your other operators. Start gathering and analyzing data from your top employees, determine why they are better, and make that part of the training.

2 Ways To Attain the Information You Need

How do you capture their knowledge and best practices? There are two options, both can get the job done. Although, one of which is obviously better than the other.

1. In-Person Observation

The first option is directly observing the operator in person while they perform their setup tasks and take written notes. This method is difficult and many details can be missed. It is also very time-consuming. Therefore, the value and potential for success with this process is limited.

2. Capture Data & Review with Operator

The second option starts with gathering and visualizing data directly from the machine while the operator is performing the setup. A good data chart is a timeline of events and activities from the machine. That chart, combined with a focused conversation with the operator, can provide some key insights.

An operations leader can pick out certain patterns in the data and discuss those with the operator. The operator can then explain exactly what they were doing at that time. During this conversation, the operations leader may find practices that make the process more efficient or yield better results than other operators. Those practices can then be codified and taught to other operators.

The process of using data and reviewing with the operator provides more accurate and valuable insights in less time than direct observation and note-taking.

What’s Next?

Now we know what we need to do and why. For the remaining parts of this article, we are going to put ourselves in this situation, and make an example of how this type of solution might work. Furthermore, we will see how much of a difference tracking this process can make, and the potential improvement on your overall manufacturing efficiency.

Setting the Scene 

In this theoretical situation, here are the details we’re working with:

  • We are a Precision Metals Company that Creates Machine Tools
  • Have High-Mix, Low-Volume Production
  • Vertical machining, CNC lathes, horizontal machines, mill-turns, and grinders
  • The focus is to keep the machine shop as productive as possible

Capture and Visualize Data from the Machine

In this situation, we are going to go with the second option that does not require constant manual data entry. Remember that this is a very simple solution. All you need is a program that can collect very basic data, a full-blown MES or IIoT solution is not necessarily required.

The first step is to connect to the machine. Potentially using a relatively universal CNC communication standard like MTConnect or the very common FOCUS2 protocol for FANUC controllers.

Gather and store the following data:
  • Machine’s Mode (Manual or Automatic)
  • Status (Running or Stopped)
  • Program Run Time with the Program Number that is Running
  • Part Count

Once connected record the data for one job that will run, even if it’s for a few days. Be sure to start recording the data before the operator starts the setup process.

Create a timeline view. It’s possible to use some basic data visualization tools too.

We also have a product called SensrTrx that can connect to nearly any machine and visualize any of the machine’s data in timeline charts. In addition, the platform provides downtime reason codes, analysis, and much more valuable data that you can gather from the plant floor. Although the information that the SensrTrx platform provides is extremely valuable, for this example we will stick to the basics.

Downtime analysis chart on the SensrTrx platform that can be utilized to improve manufacturing efficiency.

An interesting point is that for this example, the data can be raw from the machine. There is no additional contextual data needed. We most often work with additional contextual data because it significantly extends the value of the machine data. However, in this situation, the only contextual data we need is the dates/times and the job being run.

Review with the Operator

An operations leader, such as a production supervisor or someone higher up in the chain, should review the results. This person should be closely familiar with the machines and tools.

The operations leader should then review the operator’s activities in the timeline chart with the operator present. The operator can explain exactly what he was doing for particular events in the timeline. The combination of data from the machine as well as input from the operator with the data in front of them is the combination that will provide the best results possible.

The best setup operators are very efficient with their work. Their tools are well organized, they are effective in how they use their instruments for measurement, execute their procedures correctly and thoroughly, and they perform their work with a sense of urgency.

Capture insights and Start Improving Manufacturing Efficiency

One example of where the review of information turns out to be valuable could be focusing on multiple starts and stops during the setup.

This basic chart can provide the insights needed to improve manufacturing efficiency.

After a review of the timeline and some discussions, the operations leader should be able to determine that the operator was performing stop checks to ensure the cutting tools would be within tolerance limits before the job was started. This process ensures the parts will be within spec while the job is running.

The visualization could reveal that the operator was loading new tools into the turret and sections of the machine required for the job that would run for a few days. While loading each tool he was using a micrometer or caliper to check feature dimensions. This would ensure the parts produced would be within required tolerances.

What You’re Left With, and How Manufacturing Efficiency Will Get Improved

The value of the timeline along with the operator’s explanations was:

  • Have an objective source of information on the operator’s activities.
  • Have accurate measurements of those activities (how long they took) and their sequence.
  • Zooming in and out of the timeline to change the perspective; and
  • Have data on the production run after the setup to confirm the quality of the setup, during normal shift hours and in “lights-out” production hours.

The alternative to using a timeline with accurate, objective data on the operator’s activities is to visually observe the operator in real-time and takedown written notes. The operator of choice’s work is likely so smooth and well done that the details are difficult to observe. Furthermore, even more difficult to accurately capture in writing while they’re performed.

This diligent setup work done at the beginning of the job will reduce the time the operator needs to monitor and adjust the machine during the job which enables him to run more machines and jobs at once. This efficiency then decreases the downtime while the job is running and increases production.

Conclusion

As a quick summary- Gather basic data, basically just time-stamps detailing when the machine was and wasn’t producing, analyze your top-performing employee’s tendencies, and make an example out of them.

This is a great way to get your foot in the door and get started along your data-driven manufacturing journey. Once you implement a solution and strategy similar to this, you can prove to yourself just how valuable data can be to improve manufacturing processes.

In time you can scale the solution. Once you find that your machine setup times and manufacturing efficiency have greatly improved, you can move on to a different process or metric to start tracking.

Scaling the solution is of course great. It means you have made great progress and found a lot of value in the data. Implementing a solution equipped with real-time data, contextual data, numerous reporting features, and the ability to communicate with other systems can bring a lot to the table. However, what is really important is that you get started with data-driven manufacturing, and develop and stick to a strong strategy with clear goals.

This graphic shows a few different data sets. It also illustrates the vast amount of different data you can acquire with an efficient factory floor data collection process.

How “Current” is Your Factory Floor Data Collection Process?

Your Factory Floor Data Collection Process is More Important than You Might Think

How “Current” is Your Factory Floor Data Collection Process? Data runs our world today. Some of the largest and most successful companies that we see rely on enormous amounts of data to drive their business decisions. They base everything on data. Companies such as Facebook thrive off of gathering, analyzing, and acting on data they acquire from users. They know everything about the people using their platform- Where they live, where they’re from, where they worked, who their friends are, their interests, and they leverage this data for their advantage very successfully.

The same goes for the manufacturing industry. Just like how data runs our world, data runs the manufacturing industry. In recent years many companies have started to realize this. On the other hand, many companies have also deemed that modern systems that provide better and faster factory floor data are excessive, expensive, and unnecessary.

What do you think? And, what is your current process?

If You Aren’t Moving Forward, You’re Moving Backward

This quote applies to business especially. There is no treading water in business- you’re either going up or you’re going down. Furthermore, there is always (emphasis here) going to be someone willing to put in the effort to be better than you, do your job better, produce more products faster, do your job cheaper, and so on.

Competition is only growing, and if you want to get ahead or stay ahead, you have to keep innovating and keep moving forward.

The point that I am making, is that manual factory floor data collection is not cutting it anymore. Manual data entry sets you back, it’s outdated, and it consumes too much valuable time without providing sufficient value.

If you aren't moving forward, you're moving backward.

Manual Factory Floor Data Collection is like Carrying Around a Phonebook in Your Pocket

If you are still doing this today, sorry for calling you out. But chances are if I see you pulling out a phonebook to dial a phone number in public- you’re either A) really old, or B) That’s all I can think of, honestly there’s just no reason for this. Why? because it’s extremely inefficient, and there is a much better, widely available solution today. Even the most basic phones have a digital contact list that you can scroll through and make a call within a few seconds. Phone book.

The question is, why would it be any different within the manufacturing industry? Why would manual data entry be an acceptable solution? I understand that you have to start somewhere and that investing in a real-time data solution such as an MES is a larger investment than a basic $100 phone. However, if you are innovating and trying to compete, this should at the least be a goal that your company is working towards. Start small, think big, but you have to start.

Work towards modernizing your system, strive to be ahead of the curve. The old ways of manufacturing and manual data entry might seem to be okay for right now today. With that being said, in the coming years when it’s standard to have a higher level of factory floor data collection and more efficient processes, it will be detrimental to the ones who choose to ignore.

What is Your Current Factory Floor Data Collection process?

Prepare yourself for a lot of questions here.

Where would you put yourself today? How do you currently collect data from the factory floor? Do you collect manually with pen and paper? Maybe a whiteboard reporting system? A starter kit that records some basic factory floor data for you? Or, are you more advanced, recording data with an IIoT or MES solution?

For whichever factory floor data collection process you are currently using, what are you doing to progress to the next step? Where does your data end up once it’s collected? Are you acting on the data you gather?

Are you content with your current process? Should you be content with your current process?

Here are some questions that you can ask yourself to help determine how efficient and detailed your current factory floor data collection process is:

  • How long does your process take? Starting from gathering data, to making an adjustment, to determining whether that adjustment improved efficiency, did nothing, or decreased efficiency.
  • Are you aware of your own biggest inefficiencies?
  • Can you accurately determine where your downtime is coming from, and how much downtime you encounter in a period of time?
  • Do you know your own biggest downtime reasons?
  • How efficient or inefficient are your change-overs? (for products and people)
  • Are your maintenance schedules optimal? How do you know?
  • Does your factory produce excessive scrap and waste? Do you know how much?
  • Is your data validated and accurate? Do you completely trust your own data?

Based on your answers to these questions, evaluate where you are today, and determine what your plan for the future should be.

The Best thing that You Can Do to Improve Your Companies Factory Floor Operations

I’ve previously mentioned that you should always be working towards improvement. A goal for factory floor data collection should be to end up with a solution that provides real-time visibility into the plant floor, with all of the data coming from one source, one version of the truth. The data should also be readily available to consume for each person within the organization.

With that being said, that is the goal for the technology. To keep moving forward, you have to equip yourself with the right tools. However the ultimate goal is more sales, and more revenue, right (You should be saying yes)? To advance in these areas you need to focus on your business challenge FIRST. Business challenge first, and leverage solving the technology challenge to be the catalyst to help you achieve your ultimate goal. 

Establish a proactive data-driven culture among the people in your company. Encourage your employees to act on the data they see, use it to make real improvements, and use it again to gauge results.

Start Small, Think Big

Easier said than done, it’s an investment to move towards a real-time data solution. It should be carefully thought about and planned out before jumping to conclusions. With that being said, data is the future. An efficient process and solution for data collection can be extremely valuable for companies who utilize it correctly.

Start with a pilot project. Connect to just 1 or 2 machines. Start with gathering real-time data on 1 or 2 manufacturing processes on the plant floor, and go from there.

At Ectobox, we have been through this process numerous times, and we recommend that companies start out small with this type of project.  To keep it very, very simple for this post, here is the process-

  • Define the Business Challenge
  • Start with a Small Project
  • Prove the Value
  • Scale when Appropriate

You don’t have to make a huge upfront investment, what is important though, is that you get started with proper and efficient data collection and take advantage of the technology available today. In doing so, you are preparing yourself for the future and ensuring that you don’t fall behind.

This image illustrates a factory with smart technology. The image represents the benefits of smart manufacturing.

3 Vital Benefits of Smart Manufacturing

3 Vital Benefits of Smart Manufacturing

There’s an extensive list of smart manufacturing benefits and many ways that smart manufacturing can add value to a company. Today, there is a “smart” everything and manufacturing companies are not getting left behind on this trend. Technology continues to advance at a quick pace in the 21st century. We have smartphones, smart TVs, but that’s old news at this point. Now we have smart lightbulbs, smart toasters, smart dental floss dispensers. Yeah, I’m not kidding, go ahead and look it up yourself.

10-15 years ago, you didn’t need to have a smartphone. It was cool to have and useful to a lot of people, but you weren’t weird or behind the times if you didn’t have one. Flash forward to today, you are completely lost without a smartphone. Can’t do a quick google search from your pocket-sized computer? Can’t check your email? Get directions anywhere in the world? We can’t live without these things today. Smartphones started as a cool option for people that wanted to spend a little extra money, now nobody can function without them.

Old phone showing how the world has changed into a "smart" everything.My point being, the world is getting digitized, the world is getting “smart.” The manufacturing sector is no exception. Many manufacturers still choose to ignore the benefits of smart manufacturing, IIoT, and Industry 4.0, and those are ones that will get left behind. Just like that big, bulky Nokia 3310 you used to carry around.

In this article, I will go over a few key benefits of smart manufacturing that you should be implementing in your factory today so that you can “future proof” your company.

1. Increased Plant Floor Efficiency with Real-time Data

Every manufacturer needs to focus on increasing efficiency. Nobody has a completely perfect process, or anywhere near one. There will always be places to squeeze out more throughput, increase capacity, cut back on downtime, etc. Manufacturers need to have a continuous improvement mindset. Be proactive about making improvements on the plant floor, and establish that type of culture among the company.

  • Make Quick Decisions and Take Action

It’s really hard to make improvements that actually help when you don’t have much substance or information to base your decisions on. Furthermore, it’s tough to measure success without seeing the numbers. How do you really know if the adjustment you made helped or not? If it did help, how much did it help?

This is where smart manufacturing benefits you and can step in to lend a hand. IIoT and manufacturing analytics systems are smart manufacturing solutions that are equipped with the ability to deliver real-time data. Real-time data gives you the substance to make quick decisions and then act on those decisions to make quick adjustments on the plant floor. Then, measure the success instantly with, again, real-time data.

  • Don’t Get Stuck in the Past

Don't get stuck in the past, focus on the future.

Think about how long this process would take as well as the accuracy if you had to have someone manually gather basic data on the plant floor, and deliver that basic, hopefully accurate data to a decision-maker in a somewhat timely manner. Sort of? hopefully? That data is getting there many hours, if not a couple of days later.

This is one of the major benefits of smart manufacturing, this process can be streamlined. These types of solutions are what the “trendy” manufacturers are turning to. As I said previously, some other manufacturers are willingly choosing to ignore these advancements in technology. Soon, it won’t be “trendy”, it will be the standard. Companies will either have to adapt and change to the new ways of manufacturing, or they will watch competing companies continue to grow past them. There is always someone out there willing to do your job better, cheaper, and faster, and today, the tools are readily available for people to take advantage.

Just like the smartphone example. Yes if you have a “dumb” phone, you could drive to a gas station, buy a map, and then go find where you are trying to go. Or, with a smartphone, you could type your destination address in and be on your way in 10 seconds. It’s the same concept with smart manufacturing.

data delivered instantly in real-time, nobody walking around the shop floor handing out information, gathering information, no operators stopping work to write down their data during a shift. Not only is this a slow and inefficient process, but it’s also poor communication, how often does that data get to anybody else on the plant floor? especially in a timely manner for that data to actually be useful.

2. Seamless Communication

Our second key smart manufacturing benefit is communication. This is one that not many people really talk about or make a big deal about. However, smart manufacturing revolutionizes the way people communicate with workmates, customers, machines, and data.

This image illustrates communication, seamless communication is one of the key smart manufacturing benefits.

Here’s why this is so important. Wasted time and wasted motion = lost production and an efficient process. This goes against lean principles, and every manufacturer should strive to become a lean manufacturer. Strive to eliminate waste and create a highly efficient environment. Smart manufacturing can have a large impact on a variety of different communication scenarios such as:

Machines to Employees:

  • Machines deliver data in real-time, constantly delivering information to operators and other employees. This information is instantly made available to each person within the company. 

Employees to Machines:

  • Employees and operators can consume real-time data to make a data-driven decision and make adjustments on the plant floor. 

Sales team to Customers: 

  • When customers call for an update on their job or a progress update, the sales representative can look at the data in real-time and give the customer an extremely accurate data-based answer with detail on how much is done, how much is left, and when they can expect delivery. With every metric being updated in real-time. 

The communication benefits of smart manufacturing are tremendous and will undoubtedly save you a headache here and there, create a more knowledgeable staff, and improve customer relationships.

Before you start tracking these types of processes, you likely don’t realize how much time and money you could be saving. We have come across clients that have told us that they have people in the company that are consistently spending half of their day running around the plant floor trying to find a certain order for a customer. What a waste of valuable time!

With a smart manufacturing IIoT / Manufacturing analytics solution, you can give customers accurate real-time adjusted numbers instead of giving a rough estimate based on your best judgment, or going to run around the shop floor to deliver an answer a few hours later.

Efficient processes = more production, more production = more time for more clients, good communication = happy customers, happy customers = return customers, and all of this = more revenue in less time.

3. Smart Manufacturing Creates more JobsThis picture illustrates the workforce problems in manufacturing.

Some people will say that automation is going to take over human jobs in manufacturing and that IIoT is going to turn everything into an automated process putting everyone out of work. This is not the case at all. While it is true that there are some jobs that will likely be largely handled by machines, IIoT and smart manufacturing creates more jobs.

It’s no secret that there is a shortage of skilled employees in the manufacturing sector. The industry is filled with a lot of people closing in on retirement. Furthermore, there isn’t a large number of young people that want to go into the manufacturing industry. What do young people want? Tech jobs (source). There is a lot of young people that want to do something related to tech. That is where everything is headed, technology drives our world today. Correspondingly, what will all of these smart manufacturers need? They will need people to fill these new jobs created by smart manufacturing and smart factories. See where I’m going here?

Manufacturers will have new needs for people who can work with new technology, software, and data.

So, no, smart manufacturing and IIoT are not going to take away manufacturing jobs. It is creating new, different jobs, jobs that might be more appealing to the younger generation. These new jobs will help boost up the manufacturing workforce, which desperately needs the help.

These three benefits of smart manufacturing are huge, and they are shaping the future of the industry. Start implementing them today. Put yourself ahead of the curve and don’t get stuck in the old ways of manufacturing.

Picture of a worker performing maintenance in a factory. Decision-makers in this factory could possibly be deciding on preventive vs predictive maintenance strategies.

Preventive Vs Predictive Maintenance for Manufacturers

Preventive Vs Predictive Maintenance for Manufacturers

Preventive vs predictive maintenance, each of these maintenance strategies will help improve the longevity of equipment. Regular maintenance will help to keep your assets healthy, reliable, and running at peak performance. Machine downtime gets expensive, even just a few minutes of downtime can be extremely costly. Putting a strong emphasis on machine maintenance will help you to avoid machine failure and reduce operational costs on the plant floor.

Whether it’s preventive or predictive maintenance, consistency is key. Maintenance is something that you have to keep up with constantly. Inconsistent maintenance can nullify all of your previous efforts, and lead to asset failure.

So what are the differences between preventive maintenance vs predictive maintenance? What are the similarities? Which one is more effective? Which one is best for you?

In the following parts of this article, we will answer each of these questions.

Preventive Maintenance

Preventive maintenace is consistent and routine scheduled maintenance of machines and assets in order to keep them running optimally and prevent expensive unplanned downtime and unexpected asset failure. A successful preventive maintance strategy requires strong stragtegic planning before a stoppage or failure occurs.

 

Predictive Maintenance 

Predictive maintenance falls in line with proactive, data-driven mainteance strategies that gather data and analyze the health and condition of an asset to assist in predicting when the asset should receive maintenance. 

The main difference between preventive and predictive maintenance is that preventive is performed on a linear schedule. With a preventive maintenance strategy, you might schedule out a work order for maintenance every 4 weeks. Then, maintenance should be performed precisely on that date, exactly 4 weeks from the last maintenance work order. Whereas predictive maintenance can be a little bit more sporadic. Predictive maintenance uses data to determine when maintenance should be performed. Consequently, maintenance will not be performed on a linear schedule. The schedule might be 3 weeks, then 6 weeks, then 2 weeks, all over the place and only performed when needed.

This makes predictive maintenance a more complex strategy. However, it also has some valuable advantages over preventive maintenance that make it worth the initial setup. We will dive deeper into the advantages later in this article.

Preventive Vs Predictive Maintenance: SimilaritiesIllustration of maintenance.

Preventive and predictive maintenance are both strategies that are planned out ahead of time, making each of them a form of scheduled maintenance.

The biggest similarity between the two is the overall goal. Both strategies are there to increase health and reliability, as well as prevent stoppages, costly downtime, and asset failure on the plant floor.

Sometimes the term preventive maintenance gets confused with predictive maintenance simply because all forms of maintenance are in place to prevent something. Technically this makes all maintenance “preventive” maintenance.

However, here’s the issue- you can use the word preventive when referring to predictive maintenance, but, when referring to preventive maintenance, you cannot accurately interchange with the word predictive. It’s better to keep the terms separate for clarity.

Preventive Vs Predictive Maintenance: Which is More Effective

Predictive maintenance is the most effective form of maintenance. There are a number of reasons for this. I mentioned earlier that predictive maintenance is more complex, but also comes with its advantages. It’s more complex because there’s more setup and technology involved. Preventive maintenance can be as simple as reading the manual for the equipment and setting up a maintenance schedule incrementally as recommended.

This type of system is similar to the way the majority of us maintain our cars. You take it into the shop, they perform an oil change, replace the oil filter, maybe some other maintenance you need. Then they tell you to come back in 3 months or 3,000 miles. There’s no data or new information behind that decision, you are scheduled to come back in 3,000 miles this time, and next time, and next time, etc.

This sounds like a proven system, right? Well, yes it is. However, just because it works, doesn’t mean that it is the most efficient system. Back to manufacturing, each machine will have a different optimal maintenance schedule.

Predictive Maintenance runs on Data

The only way that you can find the optimal schedule is by gathering and analyzing data. If you have no substance or information, it’s near impossible to make an informed decision based on what is happening on the inside of the machines. One machine might not need some type of maintenance as regularly. A different machine might be deteriorating because it needs more attention, more maintenance than the standard recommendation. However, without the data, you won’t know that the machine was unhealthy until it fails prematurely. On the other hand, if you are over-maintaining you will never know, and you will just keep unnecessarily throwing money away.

You could argue that a little bit of over-maintaining is fine. That the point of maintenance is to make sure everything is in tip-top shape all the time. While this is true to an extent, the overall goal is actually to reduce operating costs. Whether those costs are over-maintaining or unplanned downtime. So, over-spending on maintenance would be counterintuitive.

Machines are generally inconsistent and tough to accurately predict, we need a continuous flow of real-time data to help make informed data-driven decisions on the plant floor. Predictive maintenance taking advantage of real-time data is what makes it the most effective maintenance strategy.

Preventive Vs Predictive Maintenance: Which is Best for You?

Predictive maintenance is the most advanced and effective form of maintenance. However, that does not automatically mean that it’s the best option for you today. It should, at the very least, be a goal to become a completely data-driven company and include predictive maintenance in your strategy. However, not all companies are at that stage, a great number of manufacturers still choose not to implement real-time data systems such as IIoT or manufacturing analytics. There are also some companies that are trying to adapt to data-driven manufacturing but aren’t far enough along in their journey yet.

For these companies, it might be a good idea to stick to preventive maintenance in the short term. But still, start gathering small amounts of data to work towards becoming a data-driven manufacturer.

The bottom line is that you should be continually improving your process, and keep working towards creating the most efficient factory possible.