Instrumentation technologies for improving manufacturing quality

Abstract

For the past decade or more, American manufacturing has been committed to the principle of improving quality. Deming and others have defined philosophies and techniques that lead to improvement. To successfully implement such improvement, critical processes must be carefully monitored through ongoing analysis of process quality control methods. The measurements required to successfully implement statistical quality control (SQC) require more sophisticated instrumentation than simple gauging blocks and other go/no-go testing techniques. Instrumentation needs to give actual measurements, not just limit checks, and the measurements need to be supplied to some statistical calculating engine for SQC. Instrumentation technologies have continued to progress. Data acquisition systems can help to integrate process control with management information systems. Smart sensors, fieldbuses, embedded processors, artificial intelligence and other emerging technologies are becoming available for industrial control applications. There are now great opportunities for manufacturers to have much better understanding and control of their processes. Quality and productivity are dependent upon good instrumentation. The accuracy and timeliness of the instrumentation determine the information used for SQC. This information can be provided to operators in real-time and in a form appropriate for quality control. Significant cost savings are achievable.