Lean Article

Anthony Murphy’s picture

By: Anthony Murphy

Kendrick Plastics is an IATF/TS 16949-certified, tier one and tier two supplier of interior decorative trim components and assemblies to the automotive industry. Located in Grand Rapids, Michigan, its 300,000 sq ft engineering and manufacturing facility has more than 50 presses serving fully automated paint lines and assembly stations.

After being spun off from its previous ownership, Kendrick Plastics needed to scale down from a multinational system to a middle-market regional system. Using multiple software systems to facilitate manufacturing operations was inefficient and uncompetitive for a business of its scale; doing so absorbed valuable resources across departments, including manual data reconciliation, IT support for hardware and software management, and limited quality tracking and visibility. This software environment created data silos, leading to issues with synchronization that resulted in high costs and limitations on Kendrick’s ability to innovate.

One of the manufacturer’s top priorities was to find business systems that would support its new organization. Up until that point, the company had operated using 27 software systems. Though change is always challenging, Kendrick embraced it because of the benefits it would bring.

Multiple Authors
By: Theodoros Evgeniou, Caroline Zimmerman

This isn’t a new story: A novel technology disrupts society, bringing with it many benefits but also major risks and costs. We saw it during the Industrial Revolution, which vastly improved the average living standard but also led to poor labor conditions and environmental degradation, all within a timeline that was difficult to foresee.

And here we are now at the dawn of the AI revolution. This time, cloud computing and computer processing power, cheap storage, new algorithms, as well as new product and service innovations, are poised to bring about driverless cars, virtual reality, AI-enabled medical diagnostics, and predictive machine maintenance.

In tandem with the positive technological breakthroughs, however, we also see some negative, often unintended consequences of these technologies. They run the gamut of fake news and algorithms that favor the incendiary and divisive over the factual, to major privacy breaches and AI models that discriminate against minority groups or even cost human lives.

Emily Newton’s picture

By: Emily Newton

Welding technology has progressed over the years, thanks to innovations that improve accuracy and overall productivity. Some advances have been in welding automation handled by advanced robots. Other breakthroughs rely on artificial intelligence (AI) and machine vision for better defect detection. Here’s a closer look at how those two technologies have helped the industry move forward.

Welding automation reduces human labor needs

One of the reasons for manufacturers’ interest in welding technology is that it could solve or at least ease labor shortages. According to the American Welding Society, more than 50 percent of human-created projects require some type of welding. Additionally, American Welding Society data forecast 400,000 unfilled welding jobs by 2024. Some analysts believe the shortage could surpass that figure.

Training programs make younger generations aware of their opportunities in welding roles. Such programs are good starts, but they won’t bring about an immediate change. AI-powered robots could assist with the deficit in the meantime.

Anthony D. Burns’s picture

By: Anthony D. Burns

I’m a chemical engineer. The fundamentals of the chemical engineering profession were laid down 150 years ago by Osborne Reynolds. Although chemical engineering has seen many advances, such as digital process control and evolutionary process optimization, every engineer understands and uses Reynold’s work. Most people have heard of the Reynolds number, which plays a key role in calculating air and liquid fluid flows. There are no fads. Engineers use the fundamentals of the profession.

Fads, fads, fads

By contrast, in the past 70 years, “quality” has seen more than 20 fads. The fundamentals have been forgotten and corrupted. Quality has been lost. Quality managers engage in an endless pursuit of magic pudding that will fix all their problems.

Alarmingly, the latest “quality” fad, Agile, has nothing to do with quality. It’s a software development fad that evolved from James Martin’s rapid application development (RAD) fad of the 1980s. This in turn grew into the rapid iterative processing (RIP) fad. When it comes to quality today, anything will do, no matter how unrelated.

Multiple Authors
By: Sybil Derrible, Juyeong Choi, Nazli Yesiller

Communities across the U.S. Southeast and Midwest are assessing damage from the deadly and widespread tornado outbreak on Dec. 10–11, 2021. It’s clear that the cleanups will take months and possibly years.

Dealing with enormous quantities of debris and waste materials is one of the most significant challenges for communities in the wake of natural disasters. Often this task overwhelms local waste managers, leaving waste untouched for weeks, months, or even years.

The most destructive and costliest wildfire in California’s history, the Camp Fire, killed 85 people and destroyed nearly 19,000 structures in November 2018. A year later, crews were still collecting and carrying away piles of wood, metals, appliances, contaminated soil, toxic household chemicals, and other debris and waste totaling more than 3.2 million metric tons—roughly the weight of 2 million cars.

Bruce Hamilton’s picture

By: Bruce Hamilton

In 1996, the TSSC (Toyota Production System Support Center) began working with my company to create one-by-one production capability in our product assembly. Previous to TSSC’s assistance, we’d moved the furniture and machines into cells, creating the appearance of flow production, but we lacked the problem-solving know-how and management discipline to create real flow.

Remarkably, after several months of focusing on our pilot line, it appeared that all of the pieces of the puzzle had been identified and matched, and that impediments to flow had been remediated. Our kaizen support team and assemblers had worked daily to simplify, standardize, levelize, balance, and mistake-proof assembly operations. Conveyance routes were also standardized, providing material just in time at a rate of three kits every 12 minutes to match a customer takt time of four minutes per assembly. It was now time for our first live trial of a full production day with a production goal of one product every four minutes—or 120 products by day’s end.

Cameron Shaheen’s picture

By: Cameron Shaheen

With the holidays fast approaching, manufacturers, distribution centers, and e-commerce providers are working to meet growing customer demand, while also navigating severe supply-chain disruptions and mounting labor shortages. At this point, we all had hoped to have the devastating effects of the pandemic behind us. Yet the transportation delays, rising prices, component shortages, and labor challenges facing suppliers and retailers are even worse than last year. And that’s saying a lot.

This year, with retail stores reopened and online shopping in full swing, holiday sales are projected to hit a record high. According to Deloitte’s annual forecast, e-commerce holiday sales are projected to grow 11–15 percent, and retail sales are predicted to increase 7–9 percent this year. To meet this demand, manufacturers of everything from electronics to bicycles and dolls have been ramping up production to accelerate output and prepare for the inevitable onslaught of returns after the holidays.

David Isaacson’s picture

By: David Isaacson

Within every organization, problems or incidents arise that can affect the quality of your operations. Take for example, food recalls due to improper food labeling that not only could cause sickness in humans, but also result in a hit to a company’s reputation. Or, automotive product recalls due to defective parts.

Today, given supply-chain disruptions that require broader sourcing of materials, along with a shortage of skilled workers, the chances of problems rising are increasing exponentially.

Whether causing a minor blip in productivity or tragic results, any problem should be evaluated to minimize the chances that it could occur again. And, while we read about manufacturing issues almost daily, we don’t always learn what the root cause of the problem was and how it was corrected.

Chuck Werner’s picture

By: Chuck Werner

Manufacturers should routinely ask themselves: “How do I know what my problems are?” The old-school way to answer this question was based on having the resources to produce spreadsheets of operational data and the expertise to analyze the data and understand how to respond.

This does not describe most small and medium-sized manufacturers (SMMs). They are often resource- and talent-challenged. But these conditions also are what should make adopting manufacturing execution systems (MES) so attractive to SMMs. Using an MES helps companies focus on defining, measuring, analyzing, and controlling what is actually driving the business. An MES will deliver a more holistic and detailed report of how production impacts finances.

It also provides the equivalent of expert-level resources to review operations in real time and make recommendations—but without the cost of expert-level resources.

manufacturing execution system

William A. Levinson’s picture

By: William A. Levinson

This article contends that we should replace “quality” with “value” to address an enormous array of previously unaddressed risks and opportunities. Poor quality is only one of the Toyota Production System’s seven wastes, and it is rarely the most costly one because it is also the only waste to draw attention followed by corrective and preventive action. The other wastes can hide in plain view for literally hundreds of years (as proven by brick laying) and are present 100 percent of the time as they are built into the job. Even the Toyota Production System’s seven wastes do not encompass all potential wastes.

It might even be instructive to say “value management” instead of “quality management,” and “value engineering” instead of “quality engineering.” The U.S. General Services Administration already defines value engineering as “... achieving essential functions at the lowest life cycle cost consistent with required performance, quality, reliability, and safety.” Investopedia defines value as the “ratio of function to cost.” This article will define it as the ratio of utility (i.e., what we can do with the product or service) to its overall cost.

Value = Utility/Cost

Syndicate content