Dear Gemba Coach,
We’re having an internal debate about how to involve the quality department and how to use “red bins.” Any advice?
I’d have to know more about the specifics of your company to write a meaningful response, but I can share a gemba story of a plant that struggled long with the Red Bin concept.
But first, let’s go back to basics: what do we want to use Red Bins for? The aim is to build in quality: no bad part should make it past the process that produced the defective. To do so, the lean approach is to stop and react at every defect, for two main reasons. The first is to train every operator to recognize in detail a good part from a bad part. Second, the only practical way to understand what goes wrong in the physical process (e.g. how the machine makes a bad part) is to catch the equipment as it is making defectives in order to have a closer look when figuring out what is going wrong. A murder case is much simpler to solve when you catch the assassin bloody-handed. Having to investigate after the fact is much harder (and takes much greater investigative skills).
Now, back to the gemba. This plastic injection plant heard about red bins from the corporate sensei, which triggered a heated discussion. From a previous application of “lean” (no joke), they had invested in regrind equipment right next to the presses in order to avoid going through a “monument” regrind machine and to ease the “flow of regrind back into molding”. Installing red bins to isolate bad parts was a problem because it created a break in the defective-regrind-re-use flow. Plus, the red bins would quickly overflow if the parts “stagnated” there waiting for inspection. The next question was, of course, why they did they have so many defectives in the first place? But you start where you start.
The main issue was that production and quality managers had agreed to tour all the red bins once a day, but this turned out to be difficult to do in practice. The quality manager then intervened with a forceful solution. He lined the red bins with plastic bags that gathered all the defective parts. When full, the bags were taken to a meeting room, cleared for the purpose, where the quality department would inspect all the defectives and create Pareto charts. This action triggered a surprising but quick improvement in good parts throughput: it turned out many of the “defective” parts gathered in the red bins were actually OK parts. The operators had gone into the habit of clearing the parts that accumulated on the conveyor (if the operator walked away from the station, for instance) straight into the red bin. More stringent guidance on what was a good part and what was a defective gave the plant immediate quality results.
But now the quality department was swamped with defectives to analyze. Furthermore, the actions on the head of the paretos didn’t seem to improve the overall quality performance of the presses. A queue progressively built up in the defective room, which had then to be organized as FIFO lines and all sorts of clever ideas to cover for the fact that there were not enough quality operatives to both check every defective and do the rest of the quality job. (One thing they did spot is the negative impact of regrind on quality)
The plant manager finally joined the fray, and decided to lead personally the daily red bin review – tasking production and quality to do the same on the other two shifts. With this system, the defective parts stayed in the red bin at the machine, were checked once a shift on site, and gathered at the end of the shift into a central area for regrind. The plant manager had agreed with the sensei to pick one type of defect per visit and get it solved. This quickly generated an immense action plan and triggered the involvement of engineering in the red bin reviews, but also, over a couple of months, had a spectacular impact on the plant’s overall quality level. Rather than tackling the “biggies” they had hitherto failed at solving, engineering and maintenance attacked many small things to bring the machines back to standard, and, fortunately, it worked. Still, the focus remained on “problem presses” rather than trying to understand how people were making bad parts
The shop was organized by areas with a press technician in charge of four to five presses. An operator stood behind each press to finish the part and pack it, but the operators reported directly to the shop supervisor (as did the technician) and the technician’s responsibility was limited to the machine. Life on the gemba being what it is, the technicians skillfully avoided getting involved in the red bin review, and the supervisors’ attendance was spotty. It was perceived as yet another management fad to avoid confronting the fundamental truth: the presses needed significant investment to function properly.
In order to get the technicians involved, the sensei then suggested creating a “marketplace” for each technician: one central area where the parts in the red bin would be categorized, right there on the shop floor, according to defect type. The new process was now that when the operator spotted a defect, he or she would place it into the red bin and call the area technician, who would then inspect the part and take the defective to his own personal marketplace where he would sort it by defect type – the red bin review by management would include both red bins at the press and each technician market place.
This is still a far cry from stop-at-defect (injection presses are notoriously awkward to stop), but it did create a platform for discussion between quality, supervisor and press technicians, which did contribute to drive the number of defectives down further. One thing that appeared is that the head of paretos at plant level were not reflected by the heads of the physical paretos visualized by the market place. Issues where far more localized than expected – hence the difficulty to resolve quality issues at the plant level.
The sad part of the story is that the plant did improve and get out of the red (at the start the cost of non-quality was greater than the plant’s budgeted margin), but the group did not, and it got taken over in difficult circumstances and I lost contact with the firm – so I can’t say whether they continued to improve both their quality performance and their Jidoka.
So here’s the thing: there is no one way to divide labor on quality between production, quality, maintenance, engineering – it is all dependent on the personalities and competences of the people in house. Quality, probably more than any other subject, rests on good teamwork. The key is to keep focused on the “North Star”: how close are you to getting one by one confirmation of the parts by the operators, and to conduct root cause analysis on every defective part. I realize this sounds like an impossible job and the closer you get to the mountain, the larger it seems. But that’s not the lesson I’d like to take from the previous plants’ efforts. Every time they tried something, it was kinda silly at first, and “far from the path”, but still, quality improved steadily and they learned, slowly, painfully, but steadily. Three to four years down the line, this plant’s quality performance was a benchmark for the entire group (corporate could never figure out exactly how they’d done it).
As you debate with your colleagues the specifics of what you’re trying to do with the red bins, take the time to discuss what you aim to do with the “Red Bin” tool: what do you want to achieve, how would you describe a successful Red Bin implementation. And then go back to what is practical in your current situation. My guess is you’ll find that much of the debate is fueled by departmental turf quibbles about who is in charge of what and who has the resources to do what. By focusing back on the operators and the capability to identify the root cause of every problem at every defective parts, you’ll (hopefully) be able to overcome the functional perspective and create, with your colleagues, an ad hoc Red Bin process that will both give you immediate quality improvements, and teach you some more about how to build in quality into your operations.