Real-Time Quality Management in the Automotive Industry:
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Table of Contents
I. Continuous Improvement in the Automotive Industry . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3 II. Statistical Process Control: A Scientific Methodology . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3 III. A Case Study in SPC for Continuous Improvement: Cooper Tire . . . . . . . . . . . . . . . . . . . 4
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I. Continuous Improvement in the Automotive Industry
Over the last 30 years, the manufacturing industry has undergone a notable shift in terms of pushing geographic and cultural boundaries. An increased dependence on global trade, offshore labor and a worldwide supply chain are the determining factors for where, what, when and how produced goods reach consumers in an increasingly level global playing field. This shift has been particularly prevalent in the automotive sector, as automotive manufacturers obtain parts from hundreds of suppliers, and the standards for quality are becoming more stringent. A complex organizational structure is therefore required to line up the end-to-end logistics of supply chain management, financials, customer relations and human resources. With a centrally developed and coordinated manufacturing strategy, individual facilities must execute the various tactics for quality management. In this environment, opportunities for business success can be fleeting. Even under ideal circumstances, an unforeseen, outlying factor can determine whether a company wins or loses an important contract. It is critical to establish a competitive advantage in order to simply maintain profits, let alone increase revenues. Businesses can simultaneously reduce costs and remain competitive by investing in process improvements that increase quality. For example, identifying and implementing efficiencies in