Operations Article

Takeshi Yoshida’s picture

By: Takeshi Yoshida

‘Lean” is such a convenient term; everyone uses it based on their own definition. People frequently use “lean” in place of “efficiency,” probably because it sounds more cool. Another round of cost cutting? Sure, let’s tell everyone we’re “going lean,” again.

Lean is a proven, powerful productivity approach (we probably owe post-WWII modernity and the internet age to lean), yet most people don’t know what lean is really about beyond the hype. And in this age of hyper-competition, not knowing or using tools that are proven to work is a big disadvantage.

So people should learn and practice lean. But there’s one complexity: Today’s lean is a mix-up between two different but same-sounding management concepts—lean manufacturing and lean startup. Lean startup is a recent-decade thing—it was inspired by, and hence not disassociated with, lean manufacturing, but it serves a somewhat different purpose and audience. Lean manufacturing traces its roots to Japan’s post-WWII industrial recovery with the aid of some key American industrial engineers.

Let’s clarify.

Travis Carlton’s picture

By: Travis Carlton

Whether we’re talking to a front-line operator, a plant manager, or CEO, people’s reactions to being assigned a new recurring task are remarkably similar: “Oh great—more to do.” Sound familiar?

It’s a reaction that’s common in organizations transitioning from paper-based to an automated digital process for layered process audits (LPAs), even though the end result may be a sharp reduction in defects and simpler audit processes. Although there are numerous benefits to moving from a paper-based to a mobile digital platform for your LPA program, the focus of this article is how to make the transition as smooth as possible.

Layered process audits focus on quick, straightforward elements of process inputs, helping ensure process standardization and reduce defects upstream from the point of manufacture. Automating LPAs can involve a transition process, one made easier by adopting a pilot program to help you learn as you go. Here we discuss different types of pilot programs, as well as some best practices to ensure success.

Different types of pilot programs

Most commonly, manufacturers will roll out automated LPAs on a site-by-site basis. The first acts as a test site, with the goal of bringing on additional sites once the team has refined the process.

Calin Moldovean’s picture

By: Calin Moldovean

As today’s industries and operations become increasingly more global, an effective management system is rapidly becoming an essential part of a sustainable business strategy. A management system defines how work is done, the desired results, and the controls imposed to ensure those outcomes.

Your management system certification is more than a manual and more than the certificate on the wall. It’s a critical tool that will help you meet requirements (customer, regulatory, and legal), minimize risks, strengthen your market position, protect your brand, focus on the customer, improve organizational efficiency, and reduce costs. If your certifying body is not helping you continually improve your management system performance, then you should consider transferring your certifications.

Your certified management system should bring continual improvement throughout your organization, including:

1. Stronger leadership

Ryan E. Day’s picture

By: Ryan E. Day

With more than 300 employees headquartered in a modern 150,000+ sq ft facility, Plasser American Corp. (PAC) manufactures top-quality, heavy railway construction and maintenance equipment for customers in North America. To stay competitive with international competition, PAC continually looks for ways to improve its processes and best practices.

“We made a goal to drastically reduce welding rework in the assembly area, so that all the welding of individual component parts on our frames would be done in the frame shop during initial welding,” explains Joe Stark vice president of operations and production. “At that time, we were laying out each machine we built by hand using tape measures and soap stones. Our machine-to-machine consistency just wasn’t where it needed to be which meant too much rework having to be done in the main assembly areas. We knew we needed to develop some standardization and best practices to accomplish our goals.”

Challenge

The PAC team assessed the possibility of their engineering department creating models detailing every tab, bracket, plate, etc. The idea was rejected due to the tremendous amount of engineering time that would be necessary to keep the models 100-percent accurate.

Multiple Authors
By: Nadia Naffi, Ann-Louise Davidson, Houda Jawhar

Today, the survival of many organizations depends on their plans to leverage cutting-edge artificial intelligence (AI) technologies to transform their workplaces into augmented environments.

A recent IBM study found that, as a result of AI and intelligent automation, 120 million workers will need to develop new skills or even be transitioned out of companies to different jobs during the next three years. Half of the surveyed organizations had done little to rethink their training strategies to respond to this urgency.

For that digital transformation to happen, organizations must avoid the costly “buy, not build” talent strategy that involves opting for expensive new hires instead of retraining their current employees.

William A. Levinson’s picture

By: William A. Levinson

The Automotive Industry Action Group’s (AIAG’s) and German Association of the Automotive Industry’s (VDA’s) new Failure Mode and Effects Analysis Handbook (AIAG, 2019) offers significant advances over FMEA as practiced 15 or 20 years ago.The publication is definitely worth buying because the new approach includes valuable methodology; this article will cover the most important points and highlights.

New features

The new process is qualitative rather than quantitative, which overcomes a major drawback of the previous approach. The older occurrence ratings were based on the probability of a failure, and the older AIAG manuals even tabulated recommended nonconforming fraction ranges. If, for example, the failure was 50 percent or more likely, the occurrence rating was 10 (worst possible on a 1 to 10 scale), while one or fewer per 1.5 million opportunities earned a rating of 1. These probabilities can be estimated from a process capability study, assuming that one is available; otherwise, one might easily have to guess.

Anton Ovchinnikov’s picture

By: Anton Ovchinnikov

Left to their own devices, humans tend to fall prey to biases that make them poor decision makers. For instance, among other foibles, most purchasing managers routinely under-order. In fact, past research has shown that managers are typically 10 to 20 percent off the mark when it comes to ordering the optimal quantity of products.

However, somewhat surprising, the same research has also shown that this suboptimal ordering only results in a 1 to 5 percent loss in expected profit. This conundrum has left many an executive with a dilemma. As the CEO of a medium-sized online florist shop told me: “I cannot micro-manage all my people. Before I go and intervene, I need to know the impact on my business.”

Fair point. Managers who base purchasing decisions on their gut feelings—either because they have never devised a rational ordering policy or regularly choose to override it—make a lot of mistakes. But if it only costs the firm about 1 percent of extra profit, executives may be reluctant to stir the pot. In most SMEs, a CEO’s path is strewn with seemingly juicier projects in terms of ROI.

Harry Hertz’s picture

By: Harry Hertz

‘I have been offered a significant increase in salary by another employer and am giving my two-week notice.”

My guess is that this is the most common reason given when employees quit their current job. But is salary the real reason most employees quit? I have always suspected and believed that, given a fair salary, people do not quit their jobs for money. So why do they leave?

I was recently drawn to explore this topic a little more deeply after reading an article about IBM Watson’s latest feat. A new, proprietary IBM AI algorithm can predict with 95-percent accuracy which workers are about to quit their jobs. The algorithm has been successfully deployed to predict IBM employees who are a flight risk and then to propose actions to managers to engage and retain those employees. Exploring a little further the topic of employees quitting, I discovered a recent Harvard Business Review blog by Jon Christiansen. Through looking at 15 years of data, Christiansen identified eight reasons he believes employees quit.

Aaron Fox’s picture

By: Aaron Fox

If industrial manufacturing had a buzzword of the decade, it might be “Industry 4.0.” The concept is inescapable, yet it can be hard to define, especially for small and medium-sized manufacturers (SMMs). After all, SMMs’ capabilities, needs, and budgets look very different from the large companies that often drive the latest innovations and trends. However, Industry 4.0 is so pervasive that many smaller manufacturers know more about the technologies than they might think. Below, we define Industry 4.0, then explore ways that SMMs can and do implement it already.

What is Industry 4.0?

To date, there have been four major technological trends during the past few hundred years that have revolutionized industry and manufacturing. The first was the combination of mechanization with both steam and waterpower. The second joined mass production and electricity. The third was the rise of electronic and information technology (IT) systems, and with them automation.

Penelope B. Prime’s picture

By: Penelope B. Prime

The United States and China have reportedly reached a so-called phase one deal in their ongoing trade war.

While few details have been disclosed, the agreement principally seems to involve the United States calling off a new round of tariffs that were slated to take effect on Dec. 15, 2019, and removing others already in place in exchange for more Chinese purchases of U.S. farm products.

Good news, right? The end of the trade war is nigh? Don’t get your hopes up.

Although business leaders in both countries will be temporarily relieved, the underlying tensions between them will not end easily.

As an economist who closely studies the U.S. relationship with China, I believe there are fundamental issues that won’t be resolved anytime soon.

Doing it in phases

Tariffs and other trade issues have received most of the attention during the trade war, but the more fundamental—and difficult—challenges are with lax intellectual property protection and China’s industrial policy.

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