Double-digit productivity improvements resulting from workflow redesigns and new-capital equipment investments always get a lot of attention. But over time the returns from many smaller, more methodical changes and investments can rival more highly visible projects. Total productivity maintenance (TPM), for both existing and new equipment, offers just such an opportunity.

At the heart of an effective TPM program is the core understanding that equipment can be maintained to perform reliably with high levels of quality for many years. The five pillars of TPM are autonomous care, planned maintenance, preventive maintenance, education, and quality.

For preventive maintenance and other purposes, one of the key elements of TPM is tracking overall equipment effectiveness (OEE), which combines machine availability, performance and quality metrics. Machine availability reports time lost due to planned and unplanned downtime, including setup time, in a given period. Machine performance helps identify losses due to jams and minor stoppages that result in slower speeds than what’s standard. And the quality component of OEE exposes losses due to defects or material loss.

My client, a leader in innovative rail-friction management, was recently preparing for an integrated ISO 14001/OHSAS 18001 audit, and I was asked to provide on-site training to help prepare their employees. The company and its staff are well-versed in audits, having been registered under ISO 9001 for several years. In addition to the required environmental, health, and safety (EHS) awareness training, I was also asked to provide my thoughts on what to expect during the upcoming audit.

As a certification auditor, I have noticed that those in companies who have experienced smooth audits in the past tend to approach upcoming audits with a different mentality than those who may have had less-than-ideal experiences. I’m not just talking about whether or not a company achieves certification, but rather what it ends up with in terms of meaningful results that actually help improve its management system.

This article describes a novel approach to calculating the financial aspect of overall equipment effectiveness (OEE), with the result referred to as $EE (as in monetary units). By using $EE, a management team readily can “SEE” their operation in financial terms. Employees are then better able to focus on underperforming operations to improve the bottom line.

The formula for calculating OEE is straightforward, and the product of factors (with units in per cent) is a very useful metric. In modern manufacturing, challenges arise when setting cycle time targets, measuring quality, or objectively classifying downtime. When these problems have been overcome, companies then face the issue of where to direct resources to improve the bottom line. The solution is to use $EE.

Background and practical limitations of OEE

In many businesses there is a communication breakdown between the front office and the shop floor which arises by coincidence. Because the three OEE production metrics (performance, yield, and availability) are not expressed in monetary units, daily efforts to improve processes using OEE alone do not always translate into significant bottom-line savings.

In today’s increasingly complex manufacturing operations, Murphy’s Law is only an unexpected hiccup away—anything from a data error to an errant vibration to a dulled cutting tool can undermine production. In a future with fully effective sensing and information technologies that anticipate and avert potentially harmful process spasms, however, everything that might go wrong, simply could not.

Measurement Science Roadmap for Prognostics and Health Management for Smart Manufacturing Systems, a new report generated for the National Institute of Standards and Technology (NIST) and published last month, charts a course toward this ideal. The new road map is based on input received during a 2014 workshop of industry, university, and government experts on prognostics and health management (PHM) technologies, systems, and practices.

Of all the tools in the lean toolkit, 5S is the one that has proven to be the most effective—and also the most elusive. It’s effective because the actions needed to sort, set in order, shine, standardize, and sustain mirror the deeper, critically important philosophy of thinking about value, waste, and flow with a “big picture” mindset. Once an organization has adapted lean thinking and initiated 5S projects, improvement begins to accelerate in all operational phases.

However, lasting success with 5S can also be elusive because that last “S,” representing the sustainment of the effort, must constantly be nurtured. It has been said, by Quality Digest Daily contributor Mike Micklewright, among others, that the sustain step of 5S is extremely difficult; it is, in fact, probably the hardest step of all. Successful sustainment means the difference between continuous improvement and continual improvement. The former is preferable because it reflects a steady, ever-present attitude of finding ways to do things better. The latter implies a stuttering series of start-and-stop efforts, with lots of ongoing and unnecessary course corrections.

In part one of this article, we looked at ways automation can increase quality and output while saving manufacturers money. Part two considers the ways engineers are developing production systems to take advantage of automation, which requires a different mindset than traditional mechanical engineering.

Designing machinery for a modern factory requires familiarity with robotics, information technology, and process engineering. In a very important sense, manufacturing engineers are verging into artificial intelligence, much more than just physical construction of objects.

(photo credit Creative Commons BY SA)

In the world’s largest ketchup processing plant, a robot fires a continuous stream of freshly picked tomatoes across the factory floor using compressed air. A plethora of cameras make minute observations of every tomato as it flies by, checking for ripeness and damage. As soon as a defective tomato is identified, another robot fires a precision blast of air at it, unerringly knocking it out of the stream and into a separate hopper. At the other end of the factory, the finished bottles of ketchup are packaged up and placed on pallets by autonomous forklift trucks, 24 hours a day, seven days a week.

No humans are involved.

Every industry is affected by automation. It’s not just cars that are being made by robots now. Our power plants are becoming increasingly automated. Our food is grown and processed in automated farms, storage units, and factories. Buildings are prefabricated by machines. In the modern factory, smart machines talk to each other and notify their human masters when they need attention.

In this industrial revolution, most of the human workforce is simply no longer necessary, replaced by increasingly sophisticated robots, more advanced sensors, and a more robust Internet.

Reducing waste, implementing efficiency-promoting practices, and continuously improving operations are the main goals of lean manufacturing ideology. These tasks may seem daunting for a manufacturer at the start of an improvement program, but there are many concrete steps that can be taken to shift the culture at any company.

For many companies, all it takes to dramatically increase efficiency and reduce waste is a commitment to dive right in and a willingness to try new and creative ideas to find out what works best. If you are able to simplify your manufacturing tasks, increase spatial and workflow organization, take steps to reduce errors, and listen to employees on the manufacturing floor, your company will begin to see reduced waste, improved employee morale, improved efficiency, and a greater ability to manufacture products on a predictable timetable.

The following tips can help send you on your way toward all of these goals and change the way your company operates to be ready for improvement at all times.

When people talk about U.S. Food and Drug Administration (FDA) design controls, they often place a lot of emphasis on inputs and outputs, verification, transfer, and the design history file. All good things, of course; without them, you won’t meet FDA requirements for your design controls. The problem, however, is that too often people forget to ask themselves “Why?”

Let me put it another way: Why are you creating this device in the first place? I’m assuming you want to meet a medical need of some kind. If that’s true, don’t start with what it does. Start with who it’s for.

The user’s needs are often given lip service in the medical device world, but there isn’t much emphasis on finding what those needs are. According to the FDA, all design controls should start with user needs and cascade down into the other stages of the process.

There are two things to think about when defining user needs. First, “intended use” is the general purpose—what the device does. Second, the “indications for use” describe the medical conditions your device will help diagnose, treat, prevent, cure, or mitigate.