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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.
The idea is that process improvement should not interrupt production. EVOP is a process or technique of systematic experimentation. Evolutionary Operation (EVOP) is based on the understanding that every production lot has the ability to contribute valuable information on the effect of process variables on a particular product characteristic or ...
Process–architecture–optimization is a development model for central processing units (CPUs) that Intel adopted in 2016. Under this three-phase (three-year) model, every microprocessor die shrink is followed by a microarchitecture change and then by one or more optimizations.
PIDO stands for Process Integration and Design Optimization.Process Integration is needed as many software tools are used in a multi-domain system design. Control software is developed in a different toolchain than the mechanical properties of a system, where structural analysis is done using again some different tools.
Under this model, every new process technology was first used to manufacture a die shrink of a proven microarchitecture (tick), followed by a new microarchitecture on the now-proven process (tock). It was replaced by the process–architecture–optimization model , which was announced in 2016 and is like a tick–tock cycle followed by an ...
Optimization (role-playing games), a gaming play style; Optimize; Process optimization, in business and engineering, methodologies for improving the efficiency of a production process; Product optimization, in business and marketing, methodologies for improving the quality and desirability of a product or product concept
Successive Linear Programming (SLP), also known as Sequential Linear Programming, is an optimization technique for approximately solving nonlinear optimization problems. [1] It is related to, but distinct from, quasi-Newton methods .
Multi-objective optimization or Pareto optimization (also known as multi-objective programming, vector optimization, multicriteria optimization, or multiattribute optimization) is an area of multiple-criteria decision making that is concerned with mathematical optimization problems involving more than one objective function to be optimized simultaneously.