When I attended my sister’s funeral I was amazed at all the things she had done throughout her lifetime. I was astonished at all her extra activities. For someone who had been ill for over 13 years, she really kept active. She lived to the fullest and did not waste time.

It made me start to think about all the things I do that waste time, naps and dark chocolate snacks, etc. included. You can’t blame someone else if you don’t accomplish what you wish. Time ticks on, life keeps moving.

The Dash written by Linda Ellis, published by Simple Truths http://www.simpletruths.com/dash/, is a must read or listen. In the book it explains on our tombstone will be 1946 – 2046. But it is the events in between the dash that count. There are a lot of seconds within that dash. Make them count.

To give, to live, or just be happy — no matter what your goals are. Don’t waste your seconds on anything that does not move you to this destination. My father would always say to me, “You have all the time there is” when I would say I did not have time to do all the things on his list. The matter at hand was how I spent this time. I certainly did not want to spend it cleaning the manure out of the calves’ stalls.

Live your affirmations. Be thankful. And remember, sometimes we have to do a few other things to get to the good stuff.

I am sure you have heard, “it is all about the detail”. All of our 6 Sigma events and projects start with a charter and immediately go to collecting data. I don’t mean going to the computer and looking up the scrap for the last year, though that is good practice too. I mean put an easel out on the floor and ask the operators to write down production, rework and scrap every hour, including defect codes. This requires training people doing gauge Reliability and Repeatability (R & R); otherwise I do not trust the data. The data in the computer might be close in total, but it isn’t as accurate in detail. Of course to do this you must observe the process and decide what defect codes to track, say the top 10 or 15 codes, then others that you are specifically interested in.

Small oil filter adapters for GM was a high volume die cast aluminum part. Scrap at the machine wasn’t terrible — between 5% and 7% — and assembly test stand reject was not terrible at 2% to 3%, but combined AND considering we shipped 25,000 pcs. a month, this was a hearty expense.

A team was formed and a charter was written identifying the problem as scrap and rework. The process was observed, process maps created as well as detailed elemental breakdowns of the assembly and test operation. A best practice assembly test operation was defined, operators trained and then audited. Defect codes were identified and limits established. Easels were placed at the machining and assembly/test operations. Due to the high volume of parts that we were shipping, there might be three or four assembly lines running at once so data was collected by operator, by hour (time of day), by shift, and day of week.

Quickly we saw huge variation in test stand reject rates between operators. One operator’s test stand rejects were 1/3 less than everyone else. We went directly to her and observed. She simply stated when she got a test stand reject she wiped off the sealing surface and immediately retested. We instantly changed the Standard Operating Procedure to follow her process. Our scrap rate dropped 60% overnight! An intriguing occurrence two months later saw the scrap rate on one line jump back up. The problem was a past operator returned to the area and had not been properly trained in the new process.

Wanting more savings, we reviewed all our policies and procedures. We saw that the policy was to impregnate once, if it failed, re-impregnate, and if it failed again the part was scrapped. We changed this policy to re-impregnate three times. This had mixed results and was a complete bear (think big, hairy, unreasonable beast) to control. We eventually went back to only one re-impregnation. We also tested different types of impregnation and did not see any significant statistical difference.

During this time a Design of Experiments (DOE) was being done to reduce porosity. We made some minor changes; we found some of the 800-ton die cast machines were significantly less capable. We identified the best machine for this process and assigned it as the preferred machine to run oil filter adapters. Scrap was now running half the rate of the prior year! Even at a total of 4% scrap, the porosity was still our biggest scrap dollar item.

So the 6 Sigma team restarted; a few new people, a new charter, and we continued data collection and analysis. One of the first things we did was a Value Stream Map from furnace to shipping. We quickly realized we had never investigated the reliability of the impregnation process. When we added impregnation lot # as a test stand data collection, we saw no variation for a few weeks. But then one day, one lot was twice as high. Oddly, the next day the new lot # was fine.

We started visiting our impregnator and verifying their process controls; we saw no problems. One day by coincidence, we stopped by to review their process and it was raining. We noticed that our parts were sitting out on their dock in the rain. We tracked that lot # and found the problem. We were turning inventory so fast the castings arrived at the impregnator still hot. If they got wet they absorbed moisture and the impregnation vacuum could not remove all the moisture. We changed our process to avoid shipping hot castings and ask our impregnator to not store castings outside when raining. We immediately saw another drop in test stand reject rate and scrap.

Scrap was now 75% lower than the initial levels. One part data collection, one part DOE, and one part luck. We continued to monitor the rejects because occasionally someone would change the operator or process even though the process was clearly identified on the Failure Modes and Effects Analysis (FMEA). A sudden or gradual change in results and our process controls told us where to go to look for the root cause of the change.

My wife and I recently remodeled our kitchen. We were planning on selling our lovely house in the spring and we wanted the kitchen to make a strong first impression. Our contractor / decorator commented that we wanted the kitchen to ‘pop’ when potential buyers entered the kitchen. Right, so how do we do that?

I started thinking about the sales process. So many of us offer similar products and services. What makes our specific product stand out or ‘pop’? I don’t mean gimmicks, but rather something more that will almost immediately be recognized as unique or having great value to the buyer. I am not suggesting that the buyer will go “Wow!” on the first encounter, but in the proposal stage, the buyer should see something unique that you and only you could provide.

You can provide that ‘pop’ by listening attentively in the information gathering stage of the sales process. What do they really need? Do they need something they haven’t even thought of? How are you going to solve that migraine or heartburn for them?

I love a 6 Sigma project driven by a Hoshin Chart. Hoshin Charts are a very structured method to track key characteristics, drill down the most significant Pareto distributions until you identify a low hanging apple and a potential project. These actions are often called countermeasures, or Root Cause Corrective Actions. In the 70’s & 80’s we called these charts Management by Facts with Results, or MBORs.

This engineer, driven by his Gemba walks and Hoshin Chart, identified labor as the biggest cost not at goal, and took on a project to reduce Mill Labor Costs. The real goal was to keep the labor generation / burden output with less labor, thus lowering the total burden rate at the work center.

The first target was the high volume, top 40 part numbers. The other potential area was set-up time; one operator runs more parts per machine, more parts on the fixture, faster cycle times, and less scrap.

Data was collected, analyzed and discussed. The data suggested that set-up time was a significant item. Further investigation showed that the set-ups were not pre-kitted or pre-pulled. Thus, a lot of set-up time was looking for fixtures, tools, and gauges. The data also suggested an opportunity for improvement within cycle time.

Several of the actions crossed over and helped reduce set-up time, cycle time and scrap. The major actions identified were to standardize tools, always leave five tools in the machine and in same location, and add a hitter. Standard tools allowed for capability studies on these five tools, as well as a reduction of set-up time, inspection, and scrap.

The real winner happened during capability studies. A Design of Experiments (DOE) was run on machine spindle speeds and feed rates. I am not going to tell you the results, but I can tell you on their machine, on 17-4 pre-hardened material, they found a huge opportunity by optimizing at different speeds and feeds than they had been using. Using the now standard tools and re-established speeds and feeds, all the Cpk’s — process capability measures the center tendency — were above 1.33.

The result was a $165,252 annual savings on their 10 mills. The savings resulted from:

1. lower set-up times
2. less inspection times
3. faster production times
4. less scrap
5. lower tooling cost
6. better tool life
7. less walking for the operator to the inspection area

The work reduction time for the operator resulted in another project starting, which often happens. In this instance the new project challenge was to add a washer to the cell and eliminate the next operation (wash).

An excellent project that included a lot of data collection, 3 DOE, 4 major actions, and all by following the Define, Measure, Analyze, Improve and Control (DMAIC) model.

Leadership skills start with a proactive person. If you want to grow as a person and as a leader — or simply as a team player — you must work at it. Having a plan is an obvious, yet important aspect of your skills evolving to their full potential. Keep calm and keep the faith that you have in yourself. This faith can be maintained by having a specific agenda that shows what your preferred growth looks like. Being able to measure your plan or have milestones will help you trust in your plan. If your goals are measurable, similar to tasks on a To Do list, being able to cross off your goals will only help you. Two of my personal measurable goals are arriving to work 15 minutes early each day and reading a professional magazine every week to contemplate different ways to improve.

Lastly, find a mentor and discuss your plan. The mentor is someone who is moving in the same direction as you are, and is successful in achieving his or her personal and professional goal. They “get it”. Have monthly rendezvous and touch base with your mentor to ensure you are on the right track.

Some 6 Sigma projects are so contrary to popular belief that they are really exciting to see come to fruition. Aaron Zolman’s project was to eliminate waste in the wire area or, in other words, to increase speeds, increase production, reduce wire usage, and reduce scrap. The most expensive budget item on an Electrical Discharge Machining (EDM) wire machine is the wire. The manufacturers recommend a wire speed for cutting and most people use this recommended setting.

Wire machines are more complicated than at first glance simply because they have the capability to cut at multiple angles, thicknesses, harnesses, materials, etc. They also can have wire breaks, dimensional issues, water temperature, and water cleanliness issues. On top of all of these issues, we must take into account machine and guide condition. We were not aware of any prior tests conducted to test cutting at slower wire feed rates; i.e. cut rates and accuracy remain the same, but wire feed rates are slowed by 30% to 40%.

The first order of business was to run a Design of Experiments (DOE) using different speeds on different materials and thicknesses to observe quality impact on tolerances and taper. Thick material can have a taper issue as a result of the wire eroding through the cuts. The DOE tests were conducted in random order. The objective was to be able to say with 95% confidence that the lower speed did not impact either quality or wire breakage.

The recommended speed was 10 yards per minute; we were currently running seven yards per minute. The test was run at five, six, and seven yards per minute. The DOE showed the average mean was 0.0005″. This suggested that if a part has a tolerance of greater than 0.0005″, we could run at five yards per minute. At seven yards per minute the tolerance was 0.0002″.

A significant savings was realized by lowering the average speed to 5.5 yards per minute with no sacrifice in wire breakage. There was also a 15% savings in less machine downtime due to wire spool changes, emptying the wire waste, less wear on guides, etc.

All in all, a total win and a wonderful, imaginative project.