Statistical Reliability Software
Statistical Reliability Software enables significant profit improvement by reducing downtime and virtually eliminating warranty costs.
Experience tells us that the philosophy of: "If it ain't broke, don't fix it" often leads to a false sense of well being. This philosophy may be more accurately described as: "If you think its not broken, you are missing profit improvement opportunities." Unless there is a focus on reliability, profits are very likely taking a big hit from product or process failures.
Failure do not occur at random! If they did, they would likely happen at any time. The reality is that failures occur in predictable patterns. And when they do occur, they cost money!
There are two very different - but associated - ways that failures cut profits. The first way is downtime. Downtime can get very expensive, not only in terms of lost product output, but in the labor costs associated with breakdowns. The second way is warranty costs. When your product fails to perform for customers, the costs of repairs, replacements, and returns can skyrocket.
Not surprisingly, this lack of reliability can easily be avoided by applying proven statistical quality assurance principles to your design and production processes. But that is often easier said then done.
This is typically accomplished by a seven-step process:
> Identify and study the primary failure modes. Improvement in anyone of these will improve the system.
> Synthesize the overall system reliability into a predictive model. It is essential that this model reflect reality, since it is going to be used in making decisions regarding alternative courses of action.
> Explore possible improvements in the vital failure modes. Examples of such changes might include rebuilding old equipment, redesigning components, replacing old parts, etc.
> Use the model to simulate what these changes would mean in improved system performance. Simulation is a powerful tool to supplement good judgment.
> Evaluate the cost effectiveness of these improvements. As in other engineering disciplines, this provides firm comparisons for profitable decision making.
> Implement recommendations from the study. Without making changes, improvement won't happen.
> Evaluate the success of the project and record the entire procedure for future reference and continuous improvement.