Jody Muelaner’s picture

By: Jody Muelaner

In a general sense, capability is the ability to do something. Within manufacturing, capability is given a much more specific definition. It is an expression of the accuracy of a process or equipment, in proportion to the required accuracy.

This can be applied to production processes, in which case any random variation and bias in the process must be significantly smaller than the product tolerance. It can also be applied to measurements, where any uncertainties in the measurement must be significantly smaller than the product tolerance or process variation that is being measured.

Rohit Mathur’s picture

By: Rohit Mathur

Whatever the process or type of data collected, all data display variation. This is also true in software development. Any measure or parameter of interest to our business will vary from time period to time period, e.g., number of incidents per week or month, time taken in resolving incidents, number of tickets encountered in a production support environment per month, and defect density in code.

Understanding variation is about being able to describe the behavior of processes or systems over time. This variation can be stable, predictable, and routine, or unstable, unpredictable, and exceptional. Being able to distinguish between stable or common-cause variation, and unstable or special-cause variation, helps us to decide the type of action needed to improve the process. The control chart, developed by Walter Shewhart, is the tool that enables us to do so.

Scott A. Hindle’s picture

By: Scott A. Hindle

In everyday language, “in control” and “under control” are synonymous with “in specification.” Requirements have been met. Things are OK. No trouble.

“Out of control,” on the other hand, is synonymous with “out of specification.” Requirements have not been met. Things are not OK. Trouble.

Using this language, an obvious axiom would be: Take action when the process is out of control.

The everyday use of in and out of control is, however, unfortunate for control charts, the major tool of statistical process control (SPC). Why? Because in SPC these terms speak of processes as being stable or unstable. To characterize a process as stable or unstable, process limits, from process data, are needed. Specification limits are not needed.

Given the easy-to-understand basis for the action of meeting or not meeting requirements, coupled with the risk of confusion over the terms in control and out of control, why use control charts? If you are curious to see some of the benefits in doing so, read on. Two case studies are used.

Case one: Part thickness

During a regular review meeting in Plant 17, in- and out-of-specification data on the thickness of part 64 were reviewed.

Brian Lagas’s picture

By: Brian Lagas

‘Why are our changeovers taking so long?”

If you’ve asked this question on the shop floor, more than likely you were met with blank stares by your employees. Open-ended questions like this are overwhelming, so employees try to find quick answers that don’t really address the problem. They don’t have a starting point to form an answer.

But what if you asked a question with a specific, achievable goal, such as:

“What steps can we take to reduce changeover time by 15 minutes?”

You’ve then provided your employees with a measurable goal in the form of a question. Your workers may feel empowered to answer with some hands-on suggestions for incremental changes, such as reducing setup steps or combining workstations. This in turn could not only reduce changeover time, but also significantly eliminate wait times and inventories.

This approach is often described as kaizen, or “continuous improvement,” which serves as the backbone for lean manufacturing. Kaizen uses the plan, do, check, act (PDCA) problem-solving cycle to encourage manufacturers to use small ideas to solve big problems, such as costly, time-intensive changeovers.

Multiple Authors
By: Chad Kymal, Gregory F. Gruska

During the early 1980s, GM, Ford, and Chrysler established the Automotive Industry Action Group (AIAG), a not-for-profit organization with the mission “To improve its members’ competitiveness through a cooperative effort of North American vehicle manufacturers and their suppliers.” In the late 1980s, U.S. automotive suppliers, through the auspices of the American Society for Quality (ASQ), approached the VPs of purchasing for GM, Ford, and Chrysler and explained the burden of multiple standards that were being imposed on the supply base. Not only where there multiple OEM standards, there were hundreds of tier one standards as well.

Ryan E. Day’s picture

By: Ryan E. Day

Current business conversation often focuses on data and big data. Data are the raw information from which statistics are created and provide an interpretation and summary of data. Statistics make it possible to analyze real-world business problems and measure key performance indicators that enable us to set quantifiable goals. Control charts and capability analysis are key tools in these endeavors.

Control charts

Developed in the 1920s by Walter A. Shewhart, control charts are used to monitor industrial or business processes over time. Control charts are invaluable for determining if a process is in a state of control. But what does that mean?

Nicola Olivetti’s picture

By: Nicola Olivetti

According to a report by PwC, industrial sectors worldwide plan to invest $900 billion in Industry 4.0 each year. Despite these growing technology investments, only a few technologies are significantly mature to drive measurable quality impacts. Digital visual management (DVM) is one of them, being the fundamental link that bridges the lean culture and quality management in the digital age. 

What is digital visual management?

The vast majority of all the information and communication is visual. The human brain processes visual information significantly faster than text. When a relevant image is paired with audio material, two-thirds of people retain the information three days later.

Organizations dedicated to continuous improvement take advantage of this reality and use DVM to engage staff, provide insight into key information, and to ensure improvement projects are moving forward as scheduled.

DVM collaboration consists of a well-structured and interconnected series of stand-up meetings that take place regularly before a board, where the team posts (on paper or digitally) all the information it needs to steer and improve its activity. This is applicable to any team: from permanent shop-floor teams to top management, including (geographically spread) project teams.

Doug Devereaux’s picture

By: Doug Devereaux

Artificial intelligence (AI) is widely acknowledged as a crucial aspect of what is broadly referred to as Industry 4.0. Although no one knows yet how AI will be incorporated into the next phase of the Industrial Revolution, most agree that it will allow greater connectivity between people, machines, and information technology, allowing manufacturers to better optimize processes and predict problems.

How are small and medium-sized manufacturers, which typically don’t have the time or capital it would take to test emerging technologies, supposed to evaluate how AI could impact their organization—and play a role in preparing them for Industry 4.0?

Waiting for the manufacturing sector to decide, so to speak, is certainly not an option. A delay of one, two, or five years could cause a manufacturer to be left behind. The time to act is now, but the path forward isn’t clear.

One way to address this is to evaluate AI through an ongoing transformation that many small and medium-sized manufacturers have already embraced: lean manufacturing.

Scott A. Hindle’s picture

By: Scott A. Hindle

‘Process Capability: What It Is and How It Helps,” parts one, two, three, and four, discussed Alan’s development in the field of process capability1 He’d learned about the mistakes that can be made and how to avoid them in practice to become better at his job. Alan had since passed on his learning to colleagues, one of whom, Owen, had led some successful assessments of process capability.

Dirk Dusharme @ Quality Digest’s picture

By: Dirk Dusharme @ Quality Digest

We tied up last year in a neat little bow, talking about how stories define ourselves and our work; waste is waste, no matter your political leanings; and putting numbers from the news in context.

“The Gift of Being Small”

This article by Quality Digest’s Taran March wonderfully illustrates how we, and everything we do, is influenced by our “story”—our history up to the current moment.

“ISO 14001, ISO 50001 Benefit the Environment and the Bottom Line”

No matter your views on global warming, you can't escape the fact that waste is waste. If it goes up the stack, into the water, or piles up in a corner, it’s causing harm... at least to the bottom line.

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