Monitor More than the Machine to Get the Gold

I read a good article in Modern Machine Shop today on committing to a data-driven approach to improving their production capacity and throughput, and doing that by monitoring not only the machines but also the flow of products through the plant.

This reminded me of two ideas. The first was the in the blog post from our partners and friends at SensrTrx on measuring the manufacturing process…not just the machine.

The second concept I was reminded of is the trend we’ve been seeing and that we’re trying to drive for maximizing the value from the goldmine of data buried inside the plants of manufacturing companies. I’m speaking of the progression from monitoring machines and operators for eliminating basic inefficiencies to changing how you manufacture products. It can have a massive impact on how the business runs, including production throughput, cashflow, revenue, and profit.

More Details
Manufacturers often start with Data Driven Manufacturing / IIoT solutions to monitor machines for downtime, moving to proactive maintenance, and automating production and quality data among other valuable uses. However, the value a company can get from data deep inside their operations doesn’t stop at monitoring machines and operators.

The progression goes a bit like this (with variations depending on the shop):
1) Monitor machines and operators, to get visibility to the factory floor, eliminate inefficiencies, and help operators produce more with the same effort and equipment. This helps a lot with Lean efforts and monitoring the gains from the efforts.
2) Expand and scale that solution to more machines and operators
3) Monitor the manufacturing process and use Lean to eliminate more wastes. Think about making the full process more efficient.
4) Integrate ERP and scheduling with the DDM/IIoT solution to eliminate manual data entry and data sooner.
5) Look at the larger manufacturing process and flow of products, and potentially modify how to schedule jobs. Think “8 wastes of Lean manufacturing” and working more than just improvements in cycle time at a machine. This includes looking beyond cycle time improvements on a machine and think about “load more, move faster, deliver to the next station quicker.” Add to that looking at the operations performed on the machines for the jobs or orders and start mapping routes by parts through the plant. Then modify the plant layout and flow based on the data to be more efficient.

6) Continue to monitor, measure, and improve.

Key approaches or perspectives to use now and over the long term are:
1) Strategic: start by defining the business challenge to solve and working towards what data and technology is needed, instead of trying to gather a bunch of data and then figure out what to do with it all.
2) Systems: Look at the larger picture, which includes the interactive nature of the processes, and the interdependencies.
2) Data-Driven: Use objective data from your systems to define metrics, measure progress, and share the data. Then make decisions, and most importantly take valuable action.

Breaking it Down: Building Blocks of Smart Manufacturing

A Smart Manufacturing company is a manufacturer with fully integrated solutions which empower it to be highly flexible and responsive
to changing conditions, with self-healing systems. Those capabilities enable a company to reduce costs, generate more revenue, and

increase their competitiveness in their market.

So how does it all work, and where do these capabilities come from?

The Nine Blocks that Stack Up to Smart

There are 9 technologies or building blocks that stack up to create Smart Manufacturing.

  1. IoT (Internet of Things): Taking data from sensors on machines, moving it over the internet, and converting it to valuable information to help people make decisions and drive action.
  2. Automation and robots: Using robots and software to enable machines and people to work together more efficiently.
  3. Big data: Storing and using massive amounts of machine data for data analysis to gain insights about operations and machines.
  4. AI (Artificial Intelligence): Using software tools to build models and algorithms which can learn about niche areas of your facility to distinguish between normal and critical conditions.
  5. AR (Augmented Reality): Viewing models or images overlaid onto the real world on a mobile device.
  6. Additive Manufacturing: Creating objects from 3D models by joining materials layer by layer.
  7. Modeling: Portraying or defining aspects of physical world in digital form for gauging equipment status, simulating operations, or controlling live systems.
  8. Cyber Security: Applying old and new ideas of encryption, protecting attack vectors, and combining digital with physical security tactics to protect data in motion and data at rest.
  9. Cloud: Moving away from local, on-site servers towards 3rd parties like Amazon, Google to store, service, and process data.

Stacking the Blocks

Each of these technologies can deliver value on its own. However, companies can realize exponential value by combining the technologies.

Here are a few examples:

     Predictive Maintenance

  • Technologies: IoT + AI
  • Method: AI experts create a machine learning model. IoT pulls data from machines and channels it through the model to assess probability that a part or whole machine may fail within a certain period of time.
  • Benefits: Clear identification of critical maintenance windows, resulting in up to 50% cost reduction by addressing issues only when needed but before failure.

     Robot Assisted production

  • Technologies: Robots + Automation + IoT
  • Method: A “human assistant” robot is programmed to work alongside people to handle repetitive and mundane tasks or sets of tasks. The robot is pre-programmed to handle multiple task sets. Input from IoT data (such as production data further up or down the line) directs robot to change its tasking based on real-time production needs.
  • Benefits: Increased production with existing staff and reduced pressure to hire/replace workers.

     Data-driven quality control

  • Technologies: IoT + Automation + Big Data
  • Method: Set up machines to test products immediately after a certain stage of production. Automatically analyze that data relative to product quality standards. Based on results, either trigger alarms for humans to intervene or have the equipment modify its own behavior appropriately to meet the required standards.
  • Benefits: Earlier notification of equipment problems, earlier identification of product quality issues, reduced waste and rework. Increased production of product to standards.

Choosing the Right Blocks

Some of the most exciting benefits of Smart Manufacturing come from the myriad and creative ways that new technologies can be combined and implemented. To find the right combination requires effort: thoughtful planning, employee input, and focus. But even small and mid-size companies can increase their competitive position, with access to the same building blocks as larger manufacturers.

It’s True: Custom Software Can be More Affordable than Off-The-Shelf

We talked recently with a manufacturing company that has a custom ERP system they built themselves. It performs the functions they need and it is customized to exactly the way the business runs. It’s a good fit.

Not long ago the company was purchased by a much larger conglomerate of manufacturing companies. The parent company is using SAP. They suggested getting the smaller, new subsidiary to use SAP but upon analysis, we quickly realized that the existing, custom ERP system was better for that situation, because it would have required millions of dollars to get SAP to fit the smaller company’s needs.

These are the situations we deal with every day, identifying when custom software solutions for manufacturing companies are valuable and appropriate, and then creating or customizing and implementing those solutions to fit the required business outcomes and specific, required features.

Do the Basics First in Reports and Business Intelligence

It’s like baseball. You want to focus on the fundamentals before you try the expert moves.

Let’s say you’re watching your local team slide in the standings, as we have unfortunately seen with the Pittsburgh Pirates. You’ll hear the sportscasters and managers and coaches talk about getting back to the basics before they get fancy.

It’s a solid piece of advice. If you have complex systems, and not everything is working, it’s best to keep it simple, and focus on these basics first:

1) Know your desired outcomes. What do you want to know from your software and reporting systems? How will the business benefit from tracking this data? What insights do the higher-ups need to make important business decisions?

2) Identify only the data you need to gather to get those reports. Don’t add an extra field or two because you think you might use it in 10 years. Focus on what you need now and only in the near term. There is always room for improvement LATER.

3) Create a list of issues that need to be fixed. Add details to each item such as specifically how to reproduce the issue or where it is, what is the result you’re seeing now, and what result should you see.

4) Tackle each item one by one. Make a concerted effort to not jump ahead, not to tackle only the easy ones, and not to allow yourself (or whomever is implementing) to get distracted and go off and do other things.

If you’re able to execute these basics, then you will surely climb up in the rankings and have great success.

Case in point: We are working with large manufacturing company that was acquired and is experiencing similar issues. There are some legacy software, database, and reporting systems left behind, not all of which work. We are starting our work by helping them get back to what they’re calling “ground zero”. We are identifying what business outcomes they want from the system, defining the details of what needs to be fixed, and cranking through the issues one by one until they are all fixed. Once done they’ll be really happy and will be able to have the data needed to make important business decisions. They will also be in a much better position to define and pull out new sets of data for data analysis and reporting to take the business to the next level.

How to Build a Winning IS Strategy

In the last post, The Biggest Software Mistake Your Company is Probably Making, we covered the basics of what an information systems (IS) strategy is and the importance of having one in place. This week, we’ll dive deeper into what makes a good IS strategy and how to build one for your company.

What makes an IS Strategy a “good” one?

First and foremost, it needs to be created by someone with personal understanding and experience with software and data systems. It’s not enough to have an IT leader with an understanding of hardware, networking, storage, and security to set and implement your IS strategy. Hint/workaround: If you don’t have a CIO on staff with deep software knowledge, your next best bet is to have a high-ranking staff member with required knowledge and experience take the lead.

Next, a winning strategy provides a clear definition of what the company needs to run the organization, and what software is and is not appropriate to acquire and implement. This improves the decisions that are made, preventing potentially poor IS decisions that end the end work against the company’s direction and growth, such as buying software that is too expensive or that doesn’t align with new products and services the company is providing, not staffing appropriately to support the in-house technologies.

Finally, a good IS strategy makes decisions easier for a company leader when deciding what IS actions to take to help the business grow. And it prevents the company from wasting large amounts of money and time with the wrong software or data initiatives.

How to Devise Your IS Strategy

The first question your company should ask itself is how intentional you will be about the growth of their company. Intentional growth implies creating a vision and plan for the next 5-, 10-, or 20 years. If IS decisions are made without consideration for the business plans, the results from the decisions can hold back the business, cause major disruption, and cause major losses in the business.

Once you have that vision, look for ways that IS tools and concepts can enable the success of the overall corporate strategy. You don’t need to make specific decisions on technology choices right away. Just record any ideas and organize them into an IS strategy document.

Questions to ask before you begin (query both executives and mid-level managers)

  • Does an overall corporate strategy exist? (If not, this should be created first.)
  • Does the company have a CIO (or person that is wearing that hat)?
  • Does the CIO have understanding and experience of software and data systems?
  • Do other management and leadership team members involved in making IS-related decisions understand the need for an IS strategy and how it will impact them?
  • Have IS-related decisions been made recently which have turned out to be poor decisions? (i.e., much more expensive than planned, projects failed miserably, projects made the company worse-off rather than better-off)

Quick Reference: Creating an IS Systems Strategy

  1. Establish your business goals and objectives in the form of a business plan
  2. Review current technologies in place and current IT/IS strategies
  3. Define how the business goals can better be facilitated with certain software
  4. Establish high level schedule for implementing new systems, aligning with business plan
  5. Organize the IT/IS strategy in a document
  6. Assign a senior leader to be responsible for executing the plan

The Biggest Software Mistake Your Company is Probably Making

error-blog 1 picMost companies spend a lot of time thinking about IT — information technology – which refers to computer hardware, computing capabilities, storage, transmission, security, etc. Virtually everyone works on or with a computer or electronic device of some kind. Evolving technology is “in our face” all the time. You can’t help but see colleagues with the newest gadget, smartphone, or laptop, or read headlines about what Apple is up to next, or the latest security breach. Our awareness of changing technology and the associated risks is high. So most companies, whether or not they have a CTO, have a strategy for keeping their tech up to date. For example, a company may have a policy that desktops are replaced every 5 years, laptops every two years, and smartphones are BYO. IT is often what CIOs and IT directors/managers think of first. They certainly think about and focus most of their time on IT, keeping the servers up and running.

But what often gets lost in the focus on the latest and greatest tech is the information that all that tech is managing. A company’s information is worth much more than their hardware: it represents the company’s assets, including customer lists, product information, intellectual property, and historic documentation. And it’s the information that represents the company’s growth potential for the future. So an information systems (IS) strategy – one that addresses which software a company uses and how to manage data and data transmission— is a critical part of a company’s planning. Many CIOs neglect to consider how information systems could and should support business growth.

What happens then is the tools selected, the data stored, where and how the data is stored, the quality of the data, how the software works, the functions the software performs, the reports and data analysis it provides, etc. eventually becomes cumbersome, gets in the way of business growth. People in operations as well as in IT spend more time supporting the systems than using them.

So what is an IS strategy?

An IS strategy is an approach to managing your company’s information assets with software that reflects your company’s values and best helps your reach your goals, regardless of what other companies or the rest of the market is doing. It gives you a framework for making decisions so you can be confident about what software to buy (or NOT buy), where the software should be hosted, what types of technical people you need and whether they are on staff, contracted, or brought in as vendors.

Why do I need one?

The reason you need an IS strategy one is closely related to the reason you have a corporate strategy, or a market strategy, where you make business decisions based on corporate values and goals. Only you know best what those values and goals are. There will always people advising you to choose the newest, best, or most robust software, but there really is no “one size fits all” software. Think of it like a vacation destination: say you are going to the beach, and you check GPS for directions. The “best” directions depend on your personal goals for the trip: do you want to get there as fast as possible? Or would you rather avoid congested highways? Or make a side trip to visit a friend on the way? There are many roads you can take to reach your destination, and each has pros and cons.

The same applies to an IS strategy. Is your company taking a slow, organic growth model, or aggressively pursuing growth that will result in significant changes for the company (hiring many new employees, increasing leads, transactions, production, shipments, etc.)? In a small company, operations are more straightforward and manageable. But if your company is approaching or passing the 50-employee mark, the increased size and complexity of your structure and operations necessarily leads to complexity in your IS setup and needs. The same is true and more so if your company is passing the 1,000-employee mark. That increased size underlines the need for a formal IS strategy since it becomes increasingly difficult to track and share information.

Without a clear sense of what software you need to run the organization now and in the future, you don’t have a way to know what software is and is not appropriate to acquire and implement. Without an IS strategy, CIOs may select products or allow departments to select products to address specific needs, and eventually end up with overlapping or incompatible systems, a hodgepodge of tools that don’t work well together and hold the company back by wasting valuable employee time in process and data inefficiencies. Additionally, unplanned decisions on data storage, software design architecture, locally or remotely hosted software applications, etc. can have a serious impact on the success of a business when an IS strategy is not in place.

To summarize, an IS strategy enables a business’s future plans and helps them succeed by selecting the best data storage, software, and reporting/analysis systems to achieve their business goals, and making the best software functional decisions that work in concert with a company’s overall business plan for future success.

Next Up: Find out what a winning IS strategy looks like and how to build one for your company.