Technology adoption is hard. It costs money, people’s time, and valuable resources like floor space. Digital twin, additive, and augmented reality are all transformative technologies pushing the manufacturing industry to become faster and more resilient. For some companies, transformation comes in the form of foundational technologies, such as transitioning from 3-axis to 5-axis machining, updating controllers, collecting and analyzing data from the machines, or adding an ERP system or a PLM system for engineering data. These are tools to achieve an end such as a reduction in cost or new opportunities that lead to more revenue. But what happens when the results are less than expected? What happens when there is a failure? How can a company continue to harvest value from the negative consequence? By converting data to knowledge to action. Data is still a currency to power businesses through challenging times.
In recent times, the shortages of semiconductors have had rippling effects across all industries; automotive, for instance, was hit due to the growing need for onboard electronics. But some auto manufacturers withstood the disruption with relative ease. In the April 2021 Jalopnik.com article, “Toyota Prepared For The Chip Shortage Years ago. Why Didn’t Anyone Else?” Adam Ismail discussed how Toyota was able to weather this storm: “Toyota was prepared for the microchips to dry up. Not because it had a premonition that the pandemic was coming, but because it — along with the entire Japanese car industry — went through a similar ordeal after the devastating Tōhoku earthquake of 10 years ago. Except, unlike its peers, Toyota learned from that episode and instituted policies that are allowing it to maintain a steady pace of production today.”
The idea of a lessons-learned repository is a concept everyone is familiar with, though many believe it is a trivial tool or undervalued. It’s true: A tool by itself is worthless. However, the application of the tool is where organizations begin to reap the benefits. The recent advancements in digital manufacturing have taught us that data that provides action is valuable. Applying this concept to engineering and business operations is where value can be harvested.
Capturing lessons learned sounds like an easy affair. Do you have tools in place to collect and store this information? Is the information readily accessible? Is this practice part of business and strategic processes? Capturing information can be as simple as a spreadsheet or a solution at scale, such as these implementations:
Secutor Solutions Lessons Learned Database:
NASA Lessons Learned System:
The Department of Energy has a lessons learned standard:
With the correct tools in place, the value becomes obvious when incorporating this practice into regular business cycles and capex planning. In her 2006 conference paper, “Lessons learned: taking it to the next level,” Sandra Rowe discusses this: “The final important step to ensure a successful lessons learned program is a commitment from senior level management. That commitment is visible through regular repository metrics review; action is taken to implement best practices, and support to improve negative or re-occurring project trends.” In their 2008 conference paper, “Capitalizing from past projects: the value of lessons learned,” Stephanie Trevino and Vittal Anantatmula discuss the values of business procedures and time: “Policies and procedures that are audited and enforced need to be part of an organization’s learning culture and driven from top-down (Kerzner, 2003b). Project managers should be given a sufficient amount of time to search through a lessons learned system during the planning phase. Pritchard (1997) believed that when organizations provide rewards for using lessons learned, project managers will more likely document all of their lessons learned and ensure that they will not repeat the mistakes of the past.”
So far, we have been discussing risks and failures within the factory. These disruptions are detrimental to operations and the bottom line, so it is advantageous to shift this risk to an environment where failure has less of an impact. One option that AMT has enacted is to build an in-house tabletop testbed based on consumer-grade manufacturing equipment. It currently includes a 5-axis mill and a robotic arm on a 7-foot-long metal table. In addition to the physical assets, the AMT testbed is used by the MTConnect Institute for advancing the state of digital manufacturing.
Partnerships are another way to reduce risk but harvest knowledge.
Universities. Academic institutions are eager for direct industry experience. For instance, AMT has been working with Virginia Tech to implement digital manufacturing solutions and document lessons learned for two years.
Manufacturing USA. Another organization focused on partnerships, Manufacturing USA states their core mission is to drive technology adoption. “Fostering innovation, coast to coast. Manufacturing USA consists of a national network of linked manufacturing institutes. Each has a unique technological concentration, but is also designed to accelerate U.S. advanced manufacturing as a whole.”
Manufacturing Extension Partnerships. A program run by the National Institute of Standards and Technology to connect smaller manufacturers with national resources, MEP provides local access to experts and resources to aid in risk mitigation.
The Department of Energy’s National Laboratories. Scaling up to larger and more difficult projects, the national labs are interested in supporting the manufacturing industry with skills and equipment.
“How can a company continue to harvest value from the negative consequence? By converting data to knowledge to action. Data is still a currency to power businesses through challenging times. ”
In summary, the manufacturing industry focuses on managing risk, incremental change, and adopting cutting-edge technologies that change the face of manufacturing. Some companies have an appetite for risky ventures, while others will rely on foundational technologies to grow their business. Engineering and business processes will reap the benefits of past experiences if there is data to support the future.
For more information, contact Benjamin Moses at bmoses@AMTonline.org.