Charlie Chaplin in "Modern Times" (1936)

Design for Manufacturing: If You Don’t Have Time to Do It Right, When Will You Have Time to Do It Over?

By | Manufacturing, PLM | No Comments

The High Cost of Manufacturing Errors

High costs of rework and scrap plague many manufacturing organizations across all industries and product lines. And the list of root causes—and, quite commonly, excuses and finger pointing—can be bewildering.

Most commonly, manufacturing blunders that result in rework, tool damage, and scrap are the outcome of poor design for assembly and manufacturing.

But quite often, manufacturing setbacks are caused by human errors, omissions, and plain misunderstandings in the process of transitioning a new product from design to manufacturing.

Other organizational ills, such as poor maintenance practices of manufacturing assets, unmotivated employees, and poor quality management, can add to the problem.

No matter the root cause, the impact of rework and scrap can be overwhelming, especially when a problem is discovered only when the organization is already in full volume production. About half of the causes for rework are discovered during ramp-up time, resulting in design or process changes that cascade to several design or manufacturing activities, and impact work in progress, inventory and supplier contacts, and are highly disruptive and resource intensive. Read More

Connected Assets Accelerate the Journey to Lean Manufacturing

By | Internet of Things, Manufacturing | No Comments

The Seduction of Data

Industry 4.0 promises to bring our factories to the 21st century. Thanks to the pervasive digitalization of manufacturing assets, we can now collect and track detailed manufacturing operations data. Lots of it, in real time, all the time. We can analyze it, trend it, and share it across the extended enterprise, again, in real time if we wish to.

But does having more data promise better decisions? Not necessarily. Read More

Mercedes-Benz 300 SL Coupé (1954) (Andy Warhol, 1986)

Tesla: Making Cars is Hard to Do

By | Automotive, Manufacturing | 6 Comments

Tesla Struggles to Ramp Up Manufacturing Volume, With Unintended Consequences

Ramping up an auto manufacturing line is difficult. For a newcomer, reaching efficient and lean operation at the level of Toyota and GM is extremely challenging. And, as I pointed out in the past, Tesla’s ongoing manufacturing woes are a painful proof.

In 2010, Tesla acquired the Fremont, CA NUMMI manufacturing plant previously owned jointly by General Motors and Toyota for a $42 million bargain basement deal. When I visited the Fremont plant a while ago, my host was especially proud of the junkyard price the company paid for two huge Schuler hydraulic stamping presses, which form the largest line in North America and the 6th largest in the world.

What Testa didn’t get as part of the deal is complex manufacturing knowledge and experience. Read More

Narcissus (Carravagio, C. 1597-99)

Innovation and the Inherent Bias of Technology

By | Innovation, Internet of Things, IT Strategy, Manufacturing | 2 Comments

The Imherent Bias of Technology

“Technology is neither good nor bad; nor is it neutral” declared Melvin Kranzberg.

Indeed, not only is technology un-neutral, it has an intrinsic bias. In the process of defining and implementing software to perform certain tasks and solve particular problems, the designers make many assumptions and decisions—most of which are irreversible—about the intended tasks, workflows, work environment, and user profiles. Unintentionally, the marketers and designers of software tools introduce a bias.

Douglas Allchin maintains that in itself this inherent bias does not pose a problem, but it does dictate how the technology is being used, and who can and cannot use it. Consequently, the innate bias influences the ability of the organization to realize the full value of the technology.

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The Persistence of Memory

Tesla Missed Forecast. Are you Surprised?

By | Automotive, Manufacturing | No Comments

Tesla Missed Q2 Forecast

Tesla Motors delivered 14,370 vehicles in the second quarter, missing its forecast of 17,000 units “due to the extreme production ramp in Q2 and the high mix of customer-ordered vehicles still on trucks and ships at the end of the quarter, Tesla Q2 deliveries were lower than anticipated at 14,370 vehicles, consisting of 9,745 Model S and 4,625 Model X.”

This should not come as a surprise. One of Tesla’s biggest—albeit least discussed—challenges is its struggling manufacturing supply chain.
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