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Advanced product quality planning (APQP) is a framework of procedures and techniques used to develop products in industry, particularly in the automotive industry. It differs from Six Sigma in that the goal of Six Sigma is to reduce variation but has similarities to Design for Six Sigma (DFSS).
Quality, cost, delivery (QCD), sometimes expanded to quality, cost, delivery, morale, safety (QCDMS), [1] is a management approach originally developed by the British automotive industry. [2] QCD assess different components of the production process and provides feedback in the form of facts and figures that help managers make logical decisions.
Statistical process control is appropriate to support any repetitive process, and has been implemented in many settings where for example ISO 9000 quality management systems are used, including financial auditing and accounting, IT operations, health care processes, and clerical processes such as loan arrangement and administration, customer ...
Planning data. This includes all the restraints and directions to produce such items as: routing, labor and machine standards, quality and testing standards, pull/work cell and push commands, lot sizing techniques (i.e. fixed lot size, lot-for-lot, economic order quantity), scrap percentages, and other inputs.
Manufacturing process management (MPM) is a collection of technologies and methods used to define how products are to be manufactured. MPM differs from ERP/MRP which is used to plan the ordering of materials and other resources, set manufacturing schedules, and compile cost data.
In this stage all production processes and manufacturing equipment is proofed to confirm quality and output capabilities. Critical quality attributes are evaluated, and critical process parameters taken into account, to confirm product quality. Once the process qualification stage has been successfully accomplished, production can begin.
A single sampling plan for attributes is a statistical method by which the lot is accepted or rejected on the basis of one sample. [4] Suppose that we have a lot of sizes ; a random sample of size < is selected from the lot; and an acceptance number is determined.
The Quality portion of the OEE Metric represents the Good Units produced as a percentage of the Total Units Started. The Quality Metric is a pure measurement of Process Yield that is designed to exclude the effects of Availability and Performance. The losses due to defects and rework are called quality losses and quality stops.