Jun 05 2014

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Learnings from the Manufacturing Analytics Innovation Summit

manufacturing_analytics_summitOne of the challenges we all face is how to continue to hone our craft. How do you get better at what you do, stay current with new industry best practices, or the latest innovation? A good first step is to get out of your normal routine, leave the office, plant floor or wherever you work, and surround yourself with new people that you can learn from. This can occur at a conference, a course, or simply visiting another site within your own company.

I had the opportunity to attend the IE. network’s first Manufacturing Analytics Innovation Summit in Chicago a couple weeks ago. During this event I heard 20+ speakers explain how they are using various forms of data to extract intelligence for process improvement, accelerated innovation and improved efficiency. One thing for certain, there are some very exciting projects being implemented in an incredible variety of environments to accomplish an amazing diversity of manufacturing needs across the world. As a substitute for those unable to attend, I thought I would share some of the top concepts and best practices I heard, to give you the “Cliff Notes” version of the presentations, which in actuality lasted for two days.

  • Several speakers commented on not falling into the Pareto “trap” (which is easy to do). Here is a scenario: you are tasked with identifying a root-cause analysis and have identified contributing factors that account for 80% of your out-of-tolerance event. You continue to dig down, continuing to explore those factors contributing to the bulk of the variance, until after digging down several layers, you can’t see any “smoking guns” or reason why the performance issue exists. Unfortunately, there are often no shortcuts, and the smallest factors at one level can become huge factors and a driving force of why the issue exists. An example was provided of an oil & gas refiner that was having certain batches ruined by one small, very minor process stage. Failure at this stage led to 100% failure three steps later. In aggregate, however, the initial culprit was a very minor portion of the total process.
  • Big Data is not the same as analytics. Data is a start, but if no one at your organization has any trust in the accuracy of the data, then no one will follow your recommendations or conclusions drawn from the analytics performed on the data. Get the power users on your side, gain their trust, and together you can be much more effective at performing the necessary work to actually improve efficiency
  • Supply chain visibility is difficult. According to D&B speaker Sue Sheehey, 54% of US manufacturing executives admit that their firms do not have visibility beyond Tier 1 supplier, and almost 40% of reported supply chain disruptions originate with Tier 2 or 3 suppliers. Do the math, and it is easy to see why supply chain disruptions still plague the industry. D&B’s suggestion was to instead focus on supply chain risk – what disruptions will cause you the greatest pain, disruption or production delay? Then, take a closer look at being more proactive with managing those suppliers and investing the time for more frequent interactions to ensure the production flow is optimized; predictive analytics can be helpful here.
  • Customer tastes are a big driver of NPI. Demonstrating the challenge with New Product Introduction, HP presented that 420 new products were introduced in 2012, and 310 in 2013. Wow. By their own words, HP has become almost a fashion house, based on customer demands and expectations based more on aesthetics rather that new technologies … if this is the case for HP, then it is likely the case for many other High Tech manufacturers
  • Builders need to be Lean too! As the most innovative manufacturer at the event, Balfour Beatty Construction is ahead of the curve. They are a home builder, yet are talking about Lean manufacturing, Takt times, and logistics planning. This manufacturer is trying to be proactive to see what constraints are out there to avoid; the value they bring their clients is in planning and alignment – hammer time is the smallest part of their project!
  • Digital manufacturing is worth the investment. According to Rajeev Kalamdani at Ford Powertrain, virtual manufacturing has been a key enabler to improving responsiveness, new product introduction and operational efficiency. As a result, forecasting has become a way to predict the physical behavior of objects and systems. In a virtual world, no need to run forecasting scenarios – just change it! His recommendation: A process-based approach is recommended rather than a project-based approach to manufacturing.


I hope you find these “nuggets” interesting. If you have any comments to add, or were there at the event and have other knowledge to share, please feel free to comment below.


Gordon can be found on Google+ .

Permanent link to this article: http://www.apriso.com/blog/2014/06/learnings-from-the-manufacturing-analytics-innovation-summit/

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