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Process optimization is the discipline of adjusting a process so as to make the best or most effective use of some specified set of parameters without violating some constraint. Common goals are minimizing cost and maximizing throughput and/or efficiency. Process optimization is one of the major quantitative tools in industrial decision making.
Traditional six sigma methodology, DMAIC, has become a standard process optimization tool for the chemical process industries. However, it has become clear that [weasel words] the promise of six sigma, specifically, 3.4 defects per million opportunities (DPMO), is simply unachievable after the fact. Consequently, there has been a growing ...
Hermann J. Schmelzer and Wolfgang Sesselmann point out that the field of improvement of the three methods mentioned by them as examples for process optimization (control and reduction of total cycle time (TCT), Kaizen and Six Sigma) are processes: In the case of total cycle time (TCT), it is the business processes (end-to-end processes) and sub ...
Interior point methods: This is a large class of methods for constrained optimization, some of which use only (sub)gradient information and others of which require the evaluation of Hessians. Methods that evaluate gradients, or approximate gradients in some way (or even subgradients):
Typical methods used involve structured designs of experiments (DOE) which may result in interrupting production flow to conduct the trials or experiments. EVOP, on the other hand, is intended to introduce small changes in the process variables during normal production flow.
Process simulation is used for the design, development, analysis, and optimization of technical process of simulation of processes such as: chemical plants, chemical processes, environmental systems, power stations, complex manufacturing operations, biological processes, and similar technical functions.
BPR is a powerful tool that can be applied to various industries and organizations of all sizes, and it can be achieved through various methodologies and techniques, such as process mapping, process simulation, and process automation. Organizations re-engineer two key areas of their businesses.
Stochastic optimization (SO) are optimization methods that generate and use random variables. For stochastic optimization problems, the objective functions or constraints are random. Stochastic optimization also include methods with random iterates .
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