Quality Digest employees work for free. Our offices are donated. We don't pay for electricity. That’s fake news. Real news COSTS. Please turn off your ad blocker for our web site.
Our PROMISE: Our ads will never cover up content.
Quality improvement has stalled in manufacturing due to an inability to capture, continuously improve, and leverage performance knowledge in design and manufacturing activities. Other enterprise systems, such as project life-cycle management (PLM), fail to improve quality because they treat it as a process management problem. The fundamental challenges to achieving quality are knowledge-management and continuous-improvement issues. Recently, quality life-cycle management has received a boost from enterprise software solutions designed to change how manufacturers go about designing quality into their manufacturing processes and products.
Some statistics reported by manufacturers highlight the current dilemma in quality performance:
• Eighty percent of all quality issues are repeat issues. These are errors that have happened before and were fixed, yet the lesson learned wasn’t recalled by or communicated to another group so that preventive action could be taken.
The process potential index, or Cp, measures a process's potential
capability, which is defined as the allowable spread over the actual spread. The
allowable spread is the difference between the upper specification limit and the
lower specification limit. The actual spread is determined from the process data
collected and is calculated by multiplying six times the standard deviation, s.
The standard deviation quantifies a process's variability. As the standard
deviation increases in a process, the Cp decreases in value. As the standard
deviation decreases (i.e., as the process becomes less variable), the Cp
increases in value.
By convention, when a process has a Cp value less than 1.0, it is considered
potentially incapable of meeting specification requirements. Conversely, when a
process Cp is greater than or equal to 1.0, the process has the potential of
being capable.
Ideally, the Cp should be as high as possible. The higher the Cp, the lower
the variability with respect to the specification limits. In a process qualified
as a Six Sigma process (i.e., one that allows plus or minus six standard
deviations within the specifications limits), the Cp is greater than or equal to
2.0.
If your company is involved in manufacturing, chances are that a good portion of your company's assets include measurement and test equipment (M&TE). This includes everything from simple go/no-go plug gauges to air-pressure gauges, voltmeters, micrometers and calipers on up to very sophisticated equipment such as robotic coordinate measurement machines and scanning electron microscopes.
M&TE are those assets your company uses to make critical decisions on whether to pass or fail incoming materials, in-process work and finished goods.
Of course, M&TE itself must be periodically inspected, tested and calibrated as part of the quality process. Poor or unreliable measurements result in faulty decisions and questionable product quality. Calibration management software can be crucial to helping maintain equipment accuracy and properly calibrated testing equipment.
Calibration management software saves time, effort and money. Computerizing your calibration records makes them instantly available in the event of product quality problems or a quality system audit.
The last few years have provided ample evidence that control of food safety is critical. Recent media reports have clearly documented supply chain shortcomings that have threatened consumers’ health and safety. These ongoing problems and the need for consumer safety cry out for additional tools to dramatically reduce or eliminate risks.
Milestones in U.S. Food and Drug Law History
1883 Dr. Harvey W. Wiley becomes chief chemist for the U.S. Department of Agriculture. Campaigning for a federal law, Dr. Wiley is called the “Crusading Chemist” and “Father of the Pure Food and Drug Act.”
1906 The original Pure Food and Drug Act is passed by Congress on June 30 and signed by President Theodore Roosevelt. The Meat Inspection Act is passed the same day.
During the last 30 years, giant steps have been taken to repair the damage done to the environment by industry. In the United States and elsewhere, rivers that were once dead and filled with toxic pollutants now support fish and are being used for recreation. Humankind’s attitude toward and relationship with nature has drastically changed.
Similarly, government bodies across the globe are planning for future needs and, through legislation, helping to prevent pollution from troublesome chemicals such as lead and cadmium. Companies have figured out ways to reduce the amount of toxic chemicals from their products or manufacturing processes but face new challenges in trying to replicate performance in environmentally friendly ways.
Qing Rong Zhang (behind computer, center), a Shanghi-based quality engineer with more than 30 years of experience with automotive original equipment manufacturers and tier-one suppliers, handles an overall supplier assessment.
It’s hard not to pick up a newspaper or industry magazine or surf the internet without reading that manufacturing industries are relocating their operations to other countries. During the past couple of years, it’s been equally difficult to avoid articles concerning serious quality issues present in consumer and industrial products produced in emerging economies. Even as product lines move to China, India, and Russia, domestic companies are losing significant numbers of experienced employees throughout their organizations due to early retirement or reassignment. Diminished and often lost in this regard is the tribal knowledge of operators who know the pulse of the manufacturing process. This triple whammy of outsourcing, loss of tribal knowledge, and decrease in product quality has emphasized the need for third-party suppliers of supply chain solutions.
Excellence is a part of life, and we must strive for it, especially if our mistakes create problems for others. Mistakes are costly; they hit the bottom line. Some are costly enough to put us out of business.
The code word for a mistake-free state is quality. The process for achieving that begins long before gauges and calipers arrive on the scene. It’s a route with many stops, any of which can determine whether the final destination will be quality or the scrap heap.
The many stops look so routine and ordinary: choosing the right raw material, correct chemical formula, precise temperature, exact amount, specific tools, proper assembly procedures. The timely output of quality outcomes depends on each of these transactions. How can we ensure that they will all happen accurately and completely? The answer for me is visual thinking, which leads to visual devices and systems.
Visual devices ensure that each stop on the road to quality is executed perfectly, on time, and safely. A visual workplace doesn’t just minimize problems and mistakes; it can eliminate them completely for both final product quality and every transaction along the way.
One of the most important objectives of an internal quality audit is
measuring the effectiveness of an organization's quality management system. For
this to happen, executive management must first meet its overriding
responsibility of establishing and maintaining a system regarding quality
policy, goals, resources, processes and effective performance--including
monitoring and measuring the system's effectiveness and efficiency.
ISO 9001:2000 delineates this responsibility into three distinct areas: 4.1
General requirements, 4.2 Documentation requirements and 4.3 Quality management
principles. If an organization's executive management isn't active in these
three areas, then they won't be addressed and the quality system will be
ineffective. Let's look at them one at a time, first in terms of their meaning
and then as auditable characteristics.
During the 1920s, a British statistician named Ronald Fisher put the finishing touches on a method for making breakthrough discoveries. Some 70 years later, Fisher's method, now known as design of experiments, has become a powerful software tool for engineers and researchers.
But why did it take engineers so long to begin using DOE for innovative problem solving? After all, they were ignoring a technique that would have produced successes similar to the following modern-day examples:
• John Deere Engine Works in Waterloo, Iowa, uses DOE software to improve the adhesion of its highly identifiable green paint onto aluminum. In the process, the company has discovered how to eliminate an expensive chromate-conversion procedure. Savings: $500,000 annually.
• Eastman Kodak in Rochester, New York, learns via DOE software that it needs only to retool an existing machine instead of making a huge capital purchase for a new one. The solution means improved, light-sealing film-pack clips used by professional photographers. Savings: Setup time drops from eight hours to 20 minutes; scrap reduces by a factor of 10, repeatability increases to 100 percent and $200,000 is not spent on a new machine.
For almost 100 years of our quality journey, we increasingly pampered our customers by giving them what they wanted. Customers now assume that quality is a given. Further, in our present information age, customers are more aware of competitive suppliers, as well as suppliers with poor performance. Quality performance has peaked globally, and the faces of quality have moved from the line worker to the corporate executive. Activities that improve quality hardly yield significant benefits anymore. So what else can be done to improve business performance and delight customers?
