How to Improve Quality in Motion Control
Six Sigma methods can be a powerful tool to increase the quality and productivity of processes involving motion control.
I n any discussion about quality control, you are bound to hear the words Six Sigma. Other terms, such as "Black Belt" and "CTQ" (critical to quality) may be familiar, but how exactly do those words, and the Six Sigma quality process, apply to your motion control process?
Six Sigma has achieved dramatic results within companies like General Electric, yielding an annual return of over $100 million in quality improvement savings. But how can you make it work in your business, and where do you start?
Your first task in applying Six Sigma to a motion-control process is to understand its purpose, which is always to optimize quality and throughput.
Six Sigma is a tool that can unveil subtle problems that plague all processes, silently stealing productivity and quality. Like all processes, motion-control applications are not immune to production downtime and quality control issues. Slow machine set ups, product positioning problems, equipment failures, out-of-spec parts can all contribute to the problem. You may not know the exact cause, but you can see the negative results: low production counts, lackluster quality, customer rejection, and lost money. Six Sigma could be the solution to those problems.
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O ne of the most surprising and rewarding projects for motion-control quality at GE Fanuc was initiated in the mid-1990s, shortly after the corporate-wide commitment to Six Sigma by parent company GE. The program continues to evolve today-attesting to the enduring power of Six Sigma.
Cut your losses
Let's say you run a shop that manufactures weather-stripping products, and out of 5,000 strips cut and drilled daily, 500 strips are rejected because the cut lengths and drilled holes are out of specification. Losing 10% of production to scrap, rework, and repair translates into higher labor and materials costs to satisfy customer demand, and an increased risk of missing delivery deadlines.
So, how do you begin to correct this loss and apply Six Sigma? Actually, by having identified the problem as lost production, you also identified the place to start: the cutting and drilling area.
All Six Sigma projects begin with team building and training. For GE Fanuc, before the Six Sigma workshop begins, team members from our staff and from the customer's staff are selected to be part of a Six Sigma team. GE Fanuc's team must have a Master Black Belt (MBB) trainer, a project sales manager, and a salesperson. The MBB is responsible for training and teaching the group Six Sigma concepts and for facilitating the workshop. The project manager and salesperson organize the program logistics and maintain focus of program goals. As the customer, your team would include skilled workers, supervisors, managers, etc.-your experts on the process, which, in this case, is the cutting and drilling of components.
Following the DMAIC roadmap for Six Sigma projects, GE Fanuc divides the project into three steps: Define and Measure; Analyze; and Implement and Control.
Step one, Define and Measure , combines two major objectives. First, the Six Sigma team, outlined above, is trained in the tools and concepts of Six Sigma. Second, the tools are applied to the specific customer problem, cutting and drilling out of spec.
All Six Sigma projects start by identifying and defining a "problem statement." Developed in the Define phase, this statement defines the defects caused by the problem, identifying opportunities or benefits that can be achieved once the problem is resolved, calculating the Six Sigma baseline, establishing a Sigma target, and finally, calculating the financial impact. In the case of lost weather-stripping production and quality defects, a problem statement might look something like this:
"Part Number 1 Weather Strip is producing scrap due to out-of-spec cutting and drilling and is impacting costs, quality, and delivery of `My Company.' From January 1 through June 1, scrap represented an average of 10% of daily production rates. This causes missed schedules and increased overtime. The goal for this project is a scrap level of 0.75%."
Six Sigma dictates that process data must be measured before any improvements can begin. The team starts by creating a high-level process map followed by a detailed process map, which are used as reference points throughout this and subsequent phases. This is the stage where Critical to Quality measurements are identified to quantify performance. The Measure phase also includes identifying Key Process Input Variables (KPIVs) that affect CTQs. A Cause-and-Effect matrix is often used to identify the most important KPIVs. Lastly, a measurement system is identified to quantify results.
In a cutting and drilling process (photo, next page, CTQs would likely include holding tolerances-for example,
Analyze your measured data
All data collected from the Measure phase are then analyzed using statistical methods. The goal of step two, the Analyze phase, is to determine which variables are correlated with the defect studied, and then analyze the interactions among variables. From these data, the team can make inferences about which variables are important to the process, what the interaction is among the variables, and possibly determine specifications for the variables. So, during the Analyze phase, you might determine that quick starts and stops are causing the rubber material to stretch and bounce back during the cutting and drilling steps, thereby throwing tolerances out of specification.
At this point you may also determine that the solution lies in more accurate acceleration and deceleration control of the servo motor. This leads directly into the third and final step, Implementation and Control -the culmination for all data collection and analysis, as it applies to all the team's conclusions and to specific recommendations that will improve and control the process. This step is typically quite large in scope and may be repetitive as data analysis and improvements are performed incrementally.
To obtain more accurate start/stop control, you might decide to implement a servo motor with a digital drive that allows user setting of different acceleration and deceleration rates. As a result, stretching of the rubber material during cutting and drilling becomes less likely, with significant reduction in scrap rates due to out-of-spec dimensions.
Implementation and Control extend beyond immediate remedies to include control of the process over the long run. For many applications, this step includes a control plan and some form of "watchdog," such as statistical process control (SPC). It may also include an update on pertinent ISO Standards and additional raining, depending on the complexity of the Implementation phase. So, while Implementation and Control comprise the final Six Sigma step, they are not the end of the process. Actually, they're a launch point to begin proactive management of the process and direct its outcome.
Critical to quality (CTQs) measurements for a cutting and drilling process include holding tolerances for length and hole-to-h ole dimensions. KPIVs might include acceleration and deceleration rates.
Solving for X
While the motion-control example fits nicely into each Six Sigma step and has a simple solution, not all Six Sigma projects are so compliant. In fact, many solutions need to address areas outside the process that are not always apparent from the start.
For instance, you may have found the rubber weather-stripping material was substandard or the storage temperature following production was causing the rubber to change shape, or employees required a higher level of training to program and operate the machinery. Any number of unforeseen variables can impact product quality between the time the raw material is gathered by the supplier until the time it reaches your customer's hands.
That's the power of Six Sigma-it helps find and resolve these unknown variables. With an experienced and committed team, Six Sigma can optimize any motion-control operation and lead the way to near-perfect quality control.
Kevin Frantz is a Six Sigma leader at GE Fanuc Automation (Charlottesville, Va.).
F or more on Six Sigma methods, see Control Engineering , Jan. 1999 (pp. 62-70) and Mar. `99 (pp. 87-90, 103). A sidebar in the latter article relates Six Sigma methods to ac motor and drive production.
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