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Can Smart Manufacturing Replace the Art of Go and See?

by David Westphal
March 18, 2019

Can Smart Manufacturing Replace the Art of Go and See?

by David Westphal
March 18, 2019 | Comments (4)

Recently a client asked me to provide critical expertise on a complex manufacturing issue. Large, super-material plates are produced with a very tight flatness tolerance. The machining times for this part are measured in days, not hours. The process alone was consuming most of—and sometimes more than—the customer’s allowable quality tolerance. The lack of fundamental machine process capability often produced non-conforming material after investing hundreds of hours, and thousands of dollars of man and machine inputs. After struggling with this issue for upwards of a year, they finally called for some help.

While a team of engineering, maintenance, and operators were literally inside the machine alongside me diagnosing the underlying mechanical cause, several members of the corporate C.I. staff (Continuous Improvement) arrived to help. They spent the next half hour interrupting the process operator as they filled out a “Smart” manufacturing questionnaire.

Apparently, someone in corporate headquarters wanted to remotely watch the status of this critical process from the comfort of his or her office. “In the near future, by attaching to and digitally tracking the most important machine parameters,” these two chaps explained to the operator, “our leadership can make sure the machine is operating at optimum efficiency from anywhere in the world.”

Overhearing this conversation brought back a memory of standing next to a machine in the famed Toyota Kamigo engine plant years prior with my mentor, Mr. Tom Harada. Tom was driving home the point that continuous improvement in a manufacturing environment had to happen at the spot where the work took place. “No improvement can be made in the office” Mr. Harada explained, “One must go to the job to see what is really happening—to see, to touch, and to investigate the problem first hand.” Tom taught me to investigate machine problems directly and in person, to “Go and See” starting at the point where the part and the machine intersect, working out from there. He taught me problem-solving skills that he learned directly from Mr. Ohno, and machine tool experts, and others—skills for which I am forever grateful.

A short while later—with some hands-on problem-solving completed inside the machine—we were able to find the root cause of a problem that had plagued the machine for over a year. A critical machine component had shifted out of alignment, causing an angular position error of the spindle to the work piece. Armed with a good understanding of the situation, physical measurements from inside the machine, and a confirmed problem hypothesis, the maintenance team quickly found an innovative method to align the tooling.

Less than an hour later, we closed up the machine, and returned it to production. The first machining passes on the part were witness to the fact that we had correctly identified the cause of the problem. With the operators and maintenance team high fiving in the background, I caught a glimpse of the two from the corporate C.I. team still looking for those key “Smart” inputs to add to their plan. I chuckled to myself knowing that by the time the machine was hooked up to the online monitoring system in a few weeks from now, it was doubtful that the “higher-ups” would ever know the story that had taken place that day. However, by being present at the machine, we solved the problem.

We all recognize that adding digital monitoring to machinery can offer some advantages for leaders. However, in today’s wired-in world, the lost art of “going and seeing” can and will separate those who truly seek, learn, and embrace lean, from those who simply talk about it. I will always go and seek the answers first hand where the problem exists. As a leader, you, your teams and your operations will be better for having taken the time to do the same. That’s what I like to call “Smart” manufacturing!

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4 Comments | Post a Comment
Michael Unmann March 18, 2019
1 Person AGREES with this comment

There is definitely merit to this opinion. The alternate theory would be a company that uses this data to proactively address issues. Maintenance issues can be fixed before they cause downtime. This may have brought the misalign axis to light earlier. Properly used, a machine monitoring system will alert the stakeholders to a problem which if required they will visit the machine to resolve the problem.

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Rob March 28, 2019

Michael makes a good point. The earlier the detection of an abnormality the better and new sensor packages can help. Manufacturing sites already make use of multiple technologies to acheive this and it will increase to all's benefit. I see this as the continual extension of the computing and communication age. What I like about this article is that it highlights that the human role should not change. Many people seem to think that detection in partnership with AI is going to fundementally change this role. I not convinced as of yet.   

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Karen Martin March 19, 2019
1 Person AGREES with this comment

Good food for thought. Technology absolutely should be used when it provides added value and doesn't introduce new problems. However, human eyeballs and hands on the work is hard to replicate.

A client who's in the process of designing a two-bin kanban system for inventory management just suggested they put Nest cameras in the storage areas to view the bins and do the ordering from afar vs. someone physically going into the storage area. I supposed it could work if the cameras are perfectly placed, but I'm doubtful it will be error-free. Still, it's worthy of an experiment to see!

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Ishan Galapathy March 22, 2019

Great story DAvid and thank you for sharing.  The team that resolved the issue from inside the machine I beleive is the real CI Team.  The corproate lads doesn't sound like they were there to help...

I think conceptually, there's no harm in headoffice monitoring plant performance remotely.  However, if they want to monitor at machine level, they are monitoring the wrong KPI.  Machine level info at best should be monitored by that team and escalated to the plant performance level. 

Corporate should only worry about at total plant performance.

 

 

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