Find the True cause of Machine Downtime with the Manufacturing Internet of Things
At machine shops, precision metal shops, metal fabricators, and other manufacturing companies machine downtime and manufacturing downtime are not good for business. Using tools such as the Manufacturing Internet of Things can help reduce this; I will explain how later in this article. Downtime can be very expensive. However, it is possible to understand the downtime and address it.
There is no shortage of tips and hints on the web and in the knowledge of your employees on how to address machine downtime. However, the real struggle is identifying what the actual downtime is.
When preparing to address manufacturing downtime it’s best to start with objectively quantifying the downtime before trying to address and reduce the downtime. The chances of success and eventual increases in production throughput go up substantially.
What is Machine Downtime?
Machine Downtime is any period when a production machine or piece of equipment is not producing a product. There are planned downtimes for tool changeovers, planned maintenance, etc., and there are unplanned downtimes. Unplanned downtime is detrimental to the production throughput and success of the manufacturing company.
Unplanned downtime could be due to equipment failure or breakdown, starvation of parts, the operator not at the machine to work with the machine, unplanned machine maintenance, lack of an available operator, and so on.
How Expensive Is It?
Manufacturing Downtime is one of the largest sources of lost production time. Some of the numbers of downtime can sound extreme but are real. For example, the average manufacturer has 800 hours of downtime per year (source). The cost of downtime per minute for various size manufacturers in the automotive industry is an average of around $22,000 (downtime-costs-auto-industry-22k-minute)…again, that’s per minute!
Getting a little more down to earth for machine shops, metal fabricators, and other discrete manufacturers, the numbers may not be as big. However, for the size of the companies, the numbers can still be significant. Let’s say for one machine the number of units produced per hour is 20. The average revenue per unit is $50. If you have 10 hours of unplanned downtime for that one machine in a month the estimated loss of revenue is $10,000. Multiply that by a few machines or more, and you’re looking at maybe $100,000 or more in lost revenue per month. That could end up being $1,000,000+ per year. Of course, the numbers at your shop will vary.
You may also be thinking, “We don’t have that much downtime. There’s no way it’s that high.” Are you really sure about that? OK, maybe it’s not. I’ll simply ask you to be open to being off a little with the numbers if you’re not measuring it in an accurate and objective manner.
Ways to Reduce Machine Downtime
There are many ways to reduce downtime… lots of tips and tricks. They include investing in preventative maintenance (or using proactive maintenance ideas), smart investments in new technology, better training for employees, empowering employees to take action on issues, perform risk audits, and collect and study data.
The lists of ways to reduce manufacturing downtime are great methods. However, in which of those areas should you spend time, energy, and money? How do you know what the causes of manufacturing downtime are? If one is to invest resources into solving a problem, it’s best to understand that problem first.
Understand Downtime First
The first step is to quantify and understand your company’s downtime could be to manually record data. However, this approach often doesn’t provide accurate, usable, and timely data. Operators and shop supervisors can record the data on a log sheet. This process, though, may be fraught with issues such as adoption issues, no time to record the data, only some of the data is recorded, or the data could be accidentally inaccurate. The log sheets are often sent to a person in the office to enter. We have often seen situations where manufacturers will get the data for machine downtime a week or more after the fact after the data is entered in Excel and analyzed. When the manager or owner then looks at the data they’ll call a shop supervisor into their office or go to the plant floor to talk with an operator. Often that person working with the downtime in question will have forgotten what happened.
How to Understand Machine Downtime
Therefore, it’s best to have a system that collects and analyzes manufacturing downtime data without any effort by humans. The technology to collect downtime data is commonplace and affordable. Therefore, the price of these solutions can be paid for often in a year or less multiple times over relative to the savings and additional revenue that comes from significantly reducing machine downtime. Additionally, solutions can be put in place in a matter of weeks, not months or years.
These solutions are using Manufacturing Internet of Things technologies which include sensors to collect data or connecting to a machines PLC or controller, a gateway computing device to preprocess and send the data to be stored and analyzed, a Manufacturing Internet of Things software platform with data storage and other capabilities, and display devices like inexpensive tablets and/or TV monitors in the plant floor.
These solutions can be set up to track data for a single machine to start, to work through technical challenges, if any, and to help with adoption by the shop floor. Those solutions can then be extended to additional machines, lines, and even plants.
Manufacturing Internet of Things
It is best to use a Manufacturing Internet of Things software platform that is an industry-standard, backed by a solid company, and which uses open standards for integrations with other products, multiple storage options, etc.
We also prefer to not use a rigid, single-use, off-the-shelf solution. Instead, we prefer to use off-the-shelf Manufacturing Internet of Things platform like ThingWorx from PTC (source). This enables us to not only address the current challenges but also to lay a technical foundation for building solutions for additional challenges in the future by following best practices and models of maturity like ISA-95.
We suggest not creating a custom software application to collect and analyze machine data. That simply isn’t a strategic move for a company. Custom software can be very expensive, much more expensive than off-the-shelf opens discussed above.
What is needed to implement the solution is multiple skillsets in your manufacturing company or from a trusted vendor to understand your challenges, correctly interpret those challenges to create the appropriate solution, and have the technical capability to create, implement, and support the solution long term.
If this blog post was valuable and if you are in this situation and want to discuss challenges your company is having around machine downtime and how to get valuable, objective data, please call us any time. We’d be happy to talk about your situation.