Genichi Taguchi - SPC and quality engineering Taguchi developed the modern day methodology behind quality engineering - an approach that involves combining engineering and statistical methods to reduce costs and improve quality by optimizing product design and manufacturing methods. Taguchi was born in 1924 in Takamachi, Japan, a city famous for the kimono industry, so it was only natural for him to study textile engineering as he was expected to assume responsibility for the family kimono business. But in 1942, Taguchi's draft notice came and with it came an interest in statistics. Under the guidance of Prof. Masuyama, at the time regarded by many as the best statistician, Taguchi's statistics skills were nurtured and honed.
Unisys- computerized insurance outsourcing business Unisys leverages unrivaled economies of scale at its global outsourcing service centers and incorporates the latest technology and business-process best practices to speed insurance processing. In addition, it delivers guaranteed unit costs for policy administration. Unisys started this business in the early 1990's and experienced a shaky start, being fined in 1996 for not meeting performance targets, in particular, percentage of claims processed in error and percentage of claims processed outside a time limit. Since 1996 Unisys has redesigned its processes and is now one of the leading providers of outsourcing services to over 400 insurance companies.
Assessing Capability to Deliver Competitive Priorities
Organizations select a service or manufacturing strategy for each market segment it supports. This is done by taking into consideration the corporate strategy and market analysis. Each process will focus on one or two competitive priorities - low cost operations, top quality, consistent quality, delivery speed, on-time delivery, development speed, customization, variety and volume flexibility. By measuring the performance of the process against the competitive priority, the gap between the strategy and actual performance can be evaluated. Changes to the process can then be introduced to reduce the performance gap. For example, in banking a credit card division may start a marketing campaign to increase its business whilst keeping costs low. The competitive priorities would be: 1. low cost operations, 2. volume flexibility, 3. top quality (error-free processing). If the bank can get all these right then it will offer the best service. If the bank found by measuring its system that it could not handle volume flexibility it would have to revise its operations strategy.
Process capability analysis is a measure of the repeatability of a process. Measurement of the process is essential. Usually charts and statistical techniques are used to display the results and observe the distribution. Where the distribution is outside limits the process is currently failing. For example, a blood testing lab's customers expect results in 60 minutes. The lab might have a nominal turnaround of 55 minutes and a tolerance of ±5 mins. Any blood tests returned between 50 and 60 minutes are within tolerance and the process is capable of delivering. Measurement will reveal the defect rate and provide an opportunity for improvement.
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