Food for Thought "If you have the right people, with good, basic values and good work ethic, you can have a tremendous journey."

Buy Now
Food for Thought 2 "The follow-up in my Food for Thought series, with more focus on my experiences with Six Sigma and Kaizen."

Buy Now: Paper Back
Buy Now: E-Book

October 21, 2014

Tips For Good Leadership Skills

Filed under: Food for thought for friends — Alec @ 1:27 pm

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.

An Exciting and Inspiring Project

Filed under: Food for thought for friends — Alec @ 1:25 pm

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.

What is FMEA exactly?

Filed under: Food for thought for friends — Alec @ 1:21 pm

FMEA is a very common acronym in the manufacturing world that stands for Failure Mode Effects Analysis. It is a design, manufacturing and quality tool used to determine the robustness of design, processes of a product as well as the process to determine the probability of success. This can also be used as a tool to regularly improve the process. An FMEA rates three items: the severity of the potential failure, the probability that it will occur, and the probability that we will detect the issue prior to shipping the product. All three of these metrics are rated on a 1 to 10 scale, with 1 being insignificant, and 10 being extremely bad. The multiple of these three creates a number referred to as Risk Priority Number (RPN).

Using the concept of FMEA and RPN we are able to look at a lot of everyday events in life and business. We often worry about some things that have a very low probability of occurrence. Of course, if the consequences are extremely severe, we may want to take a second look. Let’s use a common example,-flying in an airplane. Crashes are very severe, yet at the same time the probability is extremely low. In fact, these crashes have the lowest chance of any other form of transportation.

Rather we should focus on the few vital things that have a higher probability of occurrence and are moderate in the severity of consequence. And then utilize the detection part, or measurement part as a check or assurance that it will not happen.

In conclusion: focus on the vital few instances whose risks are considered low severity and make sure you have some detection on controls with severe consequences.

Minimizing Scrap & Test Stand Reject Rates With Rigorous Data Collection

Filed under: Food for thought for friends — Alec @ 1:18 pm

Like many Six Sigma projects, this one was driven by the combination of our customer wanting a more reliable part, and lower warranty and our company internally wanting lower scrap and lower test stand reject rates.

A team of engineers and operations professionals was formed and a charter written. When the product was initially launched scrap at the die cast machine and at the assembly test stand was in excess of 30% total. The Six Sigma team leader, Carl Jordan, did a wonderful job of identifying the history and planned future actions. The team immediately began to collect data by the hour and day, using little easels located at the machine and the assembly line, and then summarized by month, using the scrap defects codes (where the scrap was found). This required some training so all operators identified scrap as the correct defect code.

Within a few months the Pareto identified Poor Fill as the #1 defect code at die cast and trim, and Leakers as the #1 defect code at assembly. There were a lot of unidentified defects, other scrap and leakers, which suggested we might need more training or more defect codes. This resulted in defect code samples and limit s­amples for subjective defects.

The engineers looked at the die cast process and found that the shot intensifier was not working totally as designed and may not have been filling the die properly. In addition a Design of Experiments (DOE) was conducted on the die cast machine to look for solutions. Some contamination was identified as a partial problem in the assembly test area, which led to a daily cleaning procedure and storage of assembly components in clean, closed containers. Assembly grease was moved to a closed container to reduce contamination. Tests were run on both impregnated and un-impregnated parts. A cleanliness spec was developed and assemblies tested; scrap and test stand rejects were saved and evaluated. The Failure Modes and Effects Analysis (FMEA) was reviewed to ensure that based on our frequency of defects occurrence, customers would never get a defect.

The DOE was focusing on reducing Risk Priority Numbers for the customer based on scrap and customer returns. Prior Eight Disciplines Problem Solving (8D) processes were reviewed and confirmed that the problems were closed and that the corrective action was still in place. Several 8D’s were reopened and reevaluated. The original 8D’s had not identified all root causes. New limit samples were made and put at the test stand. A blow-off fixture on the test stand seal was installed.

As each of these process changes were implemented, the Pareto chart was marked to date and time, and the scrap and reject rate observed. From this tracking process, we could identify how much each change impacted the process. The two biggest issues were the die cast machine intensifier and the test stand false rejects.

All of these process changes took about 10 months to implement and verify. Scrap and test stand reject scrap dropped from 75% to 90% depending on the lot.

The key to these corrective actions? Data collection by hour and defect code as well as rigorous reviews of the data by the team, using a Hoshin chart for tracking with countermeasures

Powered by WordPress