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Decision-making in metal forming

How to manage data, information, and knowledge for better results

We live in the Information Age. But for many in manufacturing faced with costly decisions in design and manufacturing, it can seem like the Way Too Much Information Age.

Large volumes of data and information are available from myriad sources. But publishing accessibility is widespread and easy, and that creates concern about the trustworthiness of those sources and the accuracy of the information they share.

Established trade journals and respected professionals and academics are probably your most reliable sources for objective and practical information. Opinions and perspectives from new industry participants also can offer insights and refreshing ideas. But be sure to consider the motivations and experience of new people when determining the reliability of the information they offer.

So how can you effectively navigate all this information in a way that leads you to an appropriate manufacturing decision?

Decision-making 101

There are two general ways to approach decision-making. The first is to use your intuition, experience, and rules of thumb. This can lead to quick and correct decisions, but you have to remove bias from your decision-making process. The second is a more methodical approach supported by analysis and objective information.

Often the best alternative is to balance both methods to arrive at an efficient and correct decision.

Three input categories you can use to analyze activities to make good forming and business decisions are:

  1. Data – Data is a raw collection of static observations from a population. Each piece of data is a fact about an individual observation. Collecting meaningful data requires your awareness of the problem you are trying to solve, the causes of the problem, and an unbiased data selection method.
  2. Information – Information is the assembly of the selected data into a meaningful collection or analysis for better understanding the scope and context of the data as it relates to the problem being solved. Be careful to eliminate emotional bias in the compiled information. When relying on information provided by outside parties, you still must understand the scope and context of the selection and analysis process. It is up to you to know how closely the information reflects your own organization's operations and experiences.
  3. Knowledge – Knowledge is your understanding of the subject matter. What you know about your manufacturing processes and materials, plus your experiences, emotional responses to issues, education and training, and cognitive awareness of the situation under review, can help you collect the most useful data, filter it, and convert it to meaningful information. Ultimately, knowledge determines your ability to make informed and effective decisions.

Influencing Decisions With FEA

We are all aware of the many variables in sheet metal properties, lubrication, die design, tooling steels, and stamping technologies. These variables influence scrap rates, springback, thinning, splitting, wrinkling, die wear, product quality, technology investment, and equipment maintenance requirements.

To get a handle on all these variables, metal formers make many of their forming and die-engineering decisions based on the results of finite element analysis (FEA) simulations. Of course, this is a heavy burden for the simulation engineer. Failure in simulation can lead to excessive die tryout times, poor material decisions, and excessive failures and scrap during production.

The simulation engineer should have a good understanding of your organization's forming experiences and capabilities, as well as your available technologies. The data used in simulation is critical to the success of simulation results. Traditional rules of thumb often lack precision to create a meaningful simulation.

The greater your understanding of the full profile of the materials you will use, the variability of the materials across coils and mill runs, and the capabilities of your forming technologies, the better your data and simulation results and manufacturing decisions. As a result, die tryout iterations should decrease and forming operations should become more efficient at consistently forming quality components.

Better decisions and the resulting improvements in business and operational results are the products of a conscious effort to employ knowledge, intuition, data, and information. You need to understand the differences, advantages, and risks of each. Once you master logic, emotion, and objectivity, your decisions will become more productive and beneficial to your organization.

Resources

Gene Bellinger, “Data, Information, Knowledge, and Wisdom,” www.systems-thinking.org, 2004.

John Beshears and Francesca Gino, “Leaders as Decision Architects,” Harvard Business Review, May 2015.

David Weinberger, “The Problem with the Data-Information-Knowledge-Wisdom Hierarchy,” Harvard Business Review, February 2, 2010.

About the Author
4M Partners LLC

Bill Frahm

President

P.O. Box 71191

Rochester Hills, MI 48307

248-506-5873