Large-scale manufacturing companies use larger automated assembly processes including the use of heavy robotic equipment to put together large products, such as automobiles. The assembly lines in these systems have centralized control, operated by only a few workers. However, the lines, as production elements, are independent in the assembly process. Automated assembly systems are designed to perform assembly operations in a fixed manner product assembly sequence. Four types of systems/operational planning problems are significant: delivery of parts to workstations; single station system; automatic multi-station systems; and partly automation. This paper focuses on the multi-station automated system used for operational assembly.
In the world there were designed some speech recognition systems but none of these systems are dedicated to Romanian language. In the present paper are presented some specific applications for which is successfully applied a speech recognition system adapted by the author for Romanian language
Large Scale Optimization is a very well-known concept in the context new manufacturing era. There are many applications focused on supply chain and intelligent or smart manufacturing. As part of flow optimization is substituting some workplaces with robotic structures (industrial robots, manipulators, cobots, etc.). Thus, one challenge is to get a good process design, with optimum systems use, with business impact, return of investment (from financial and human resource point of view). Another challenge is to choose the kinematic structure oriented on station's requirements. The robots are particular form of automation with significant costs that increase with the number of joints. But, in the context of Industry 4.0 revolution the use and design of robots and kinematic chain workstations it changes.
Fuzzy logic was, first time presented by L.A. Zadeh in 1972 as an alternative method of classical theory control, by giving the opportunity to use a non-analytic method. During time, fuzzy logic was extensively applied in automotive, aerospace, business, electronic and even defence field, considering that is an easier way to obtain high performance. Automatic experts are constantly researching and proposing innovative and effective fuzzy control systems. The problem appears not in simulating the problem but integrating controller in an electric circuit. Therein lies the problem of the profitability of the fuzzy controller comparative to a classic PID control. Besides the time and knowledge requirements are quite different.
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