Here's how you can navigate complex problems in automotive manufacturing with logical reasoning.

I appreciate the emphasis on pinpointing the exact nature of the problem, but the reality is that in automotive manufacturing, problems often have multiple intertwined causes. Simply gathering data isn't enough; you need a comprehensive approach that integrates real-time analytics and predictive maintenance. Relying solely on historical data and logical reasoning can lead to overlooking subtle, yet critical, factors. The focus should be on a proactive strategy that anticipates issues before they arise, utilizing advanced technologies like AI and machine learning to provide deeper insights and more robust solutions.

One thing I encountered with problem resolution in manufacturing is sometimes looking beyond the shop floor. Components failing due to quality are at times contributed during logistics, specially when crossing places with different climate. These are not so evident during receiving quality inspections considering multiple quantity in one packaging. We may have rigid engineering validations and evaluations but often times how the components are packaged are missed out. Problems in manufacturing covering efficiency may sometimes be only due to line balancing especially when a new and more capable equipments are added with the existing ones operating for several years already.

As data patterns are established; aside from formulating hypothesis in the manufacturing organizational level, collaborating with design engineering can also help bring out improvement ideas since those parameters implemented in the manufacturing plant are coming straight from the design. Parameters dictated by the design together with tolerances could/might affect equipment performance in the long run.

Once you've got your hypothesis, it's game time. This is where we test out potential solutions, whether it’s running simulations, tweaking the production process, or experimenting with new materials. Make sure each test is controlled and record your results down to the smallest detail. This step is all about trial and error. Not every solution will be a winner, but each attempt gets you closer to cracking the problem. Use logical reasoning to interpret the results and figure out the best way forward.

The last part is quite often the trickiest one. Sharing the lessons learnt with the wider organisation and creating new design rules to prevent recurrence are often given a lip service as the team moves on to tackling the next pressing issue. Doing the paperwork might seem like a non glamorous thing, but is crucial in ensuring the failures don't resurface in a different?way.

After implementing the set of changes. Monitoring together with identifying the gaps between actual result and expected result must also be taken into consideration, since this is where you can gauge how effective the changes are in real world application. This can also give you a better perspective if additional actions might be needed as a final touch to ensure flawless results.

1. Gain their trust. 2. Teach them what they need to know. 3. Give them the tools they need. 4. “Create a Want” in them to succeed. 5. Get out of their way. 6. Keep a watchful eye to guide their course. 7. Shower them with praise for a job well done.