Combining powerful improvement methods in process manufacturing

Six Sigma and Lean improvement methods have been used in a number of industries for quite some time. Read here to learn how you can use both in a chemical plant and reap significant benefits.

By Douglas R. Pratt, Dow Corning Corp.

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This sequence gave birth to the acronym DMAIC, which has become synonymous with Six Sigma. Not long after applying these DMAIC principles to manufacturing, Motorola recognized that they (like Lean) could also be applied to transactional business processes.

In recent years, Six Sigma has gone beyond focused projects led by trained leaders (i.e., Black Belts) to improve existing operations. It now guides the creation of new processes, products and workflows that perform at a Six Sigma quality level. More importantly, Six Sigma generally is considered to be a leadership and management philosophy, a culture, one anchored on fact and data-based decision-making that is clearly focused on the needs and voice of the customer. (Lean also is considered a culture or management philosophy at those companies that practice it <em dash>— one that abhors waste of all kinds in all processes and drives for maximum speed.)

Strive for synergy
Many organizations struggle and debate about which methodology is best. But this is not an either-or issue. Is a wrench better than a hammer? Each tool, Lean and Six Sigma, has value. Both approaches support the larger goal of achieving product, process and operational excellence to better serve the customer. The traditional practice of Lean offers reduced waste and increased speed, whereas Six Sigma provides defect and variation reduction. Using the two methodologies and their tools together leverages the benefits of both. For those companies that have long pursued Lean, Six Sigma should be brought forward. Six Sigma companies should view and embrace Lean as a strong friend and ally.
 Many companies in industries such as automotive and aerospace that first embraced Lean are already working to incorporate Six Sigma. This is because the application of Lean often can benefit from the discipline that Six Sigma provides. For example:

• Some Lean projects have lacked a well-defined project charter with clear goals and scope; efforts have wandered without focus while scope grew to an unmanageable size. This led to early confusion and wasted team effort.
• Lean often failed to use the power of statistical analysis to determine and validate the true root cause of performance problems, both key elements and features of Six Sigma.
• Lean efforts were often undertaken on a rapid trial-and-error basis. Because of this less formal approach, many gains, such as in inventory reduction, were simply not sustained. Waste and non-value-adding activities frequently crept back into the process within a few years; it was not unusual, for instance, for inventories to quickly grow back to previous levels.

Similarly, companies that adopted Six Sigma found many projects to have Lean-type goals, such as to reduce inventory, speed workflow and eliminate non-value-adding activity. These projects really did not require the rigors of full statistical analysis. Indeed, applying the full methodology of classical Six Sigma unduly lengthened the project cycle time, frustrating project sponsors and management.

 Wise Black Belts quickly adjusted and addressed these problems with the appropriate Lean tools, such as value stream mapping, Praeto charting, value-add/non-value-add analyses, etc. No extensive control charting or design-of-experiment work was needed.

A merger of the power of each methodology was inevitable. By combining the two, the improvement project leader (Lean Expert or Six Sigma Black Belt) has a full tool kit from which to draw.

As Michael George states in “Lean Six Sigma: Combining Six Sigma Quality with Lean Speed”, “Lean Six Sigma is a methodology that maximizes shareholder value by achieving the fastest rate of improvement in customer satisfaction, cost, quality, process speed and invested capital. The fusion of Lean and Six Sigma is required because:
• Lean cannot bring a process under statistical control.
• Six Sigma alone cannot dramatically improve process speed or reduce invested capital.”

So, how can these methodologies and their respective, and often overlapping tools, be best applied in the chemical industry?

Faster and better operation
Chemical batch processing is in many regards similar to discreet parts manufacturing, long the domain of Lean. Raw materials must be brought in from suppliers. These materials are typically staged and must be loaded into equipment for processing or assembly. Later they are unloaded and packaged into finished form. Variation either in the raw materials (inputs) or the process cause variation and possible defects in the finished product (output). The rigors of Six Sigma statistical analysis can address variation at these points. The tools of Lean can be used to focus on the speed of the entire process and changeovers, from unloading dock to final shipment, thus eliminating waste in handling, movement, storage, changeovers and staging.

Because most batch processes are not dedicated to a single product, a key waste in these operations is the time spent changing over from one product to the next and the wasted product or flush media involved. Thus, many engineers and managers work to lengthen the production run to eliminate the frequency of changeovers. Unfortunately, this is the wrong approach; it drives up overall inventory because each product must then be made in large enough quantities to last the entire production cycle. The right approach is to focus on driving waste out of the changeover through time-reduction techniques and engineering, so changeovers are quicker.

Opting for frequent, but shorter, changeovers, while keeping total changeover time the same, provides several advantages:

• It enables faster cycling through the production schedule and results in lower net inventory.
• It gives staff more opportunity to build changeover expertise and skill, which further shortens the changeover time.

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