Autonomomous Manufacturing Systems Aid Manufacturers Essay

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In today’s manufacturing system, the disturbances such as tool wear, breakdown of machines, and malfunctions of robotic systems, significantly affect the productivity and cost of the products. These disturbances generally bring disruptions to operation of the manufacturing systems, especially the conventional manufacturing systems. These unplanned disturbances in manufacturing systems are commonly related to recovering time and inability to recover. Those can be classified by internal and external disturbances. Examples for internal disturbances are control system, equipment, material handling and labor; while for external disturbances are order process, stocks and suppliers [1,2]. Because of these disturbances, manufacturing companies …show more content…
2. Autonomous Principles

In general, the concept of autonomy in manufacturing systems can be recognized by its independence and decision making characteristics. AMS is designed in a decentralized way, making decisions by itself without external instructions, and performing actions by itself without external forces [1]. This allows the autonomous control system to take an action when disturbance happens, so that the ‘down-time’ can be reduced considerably. Some examples of AMS implementation are autonomous production cells, automated guided vehicles, mobile autonomous robots, movable stations, or dexterous robots with intelligent sensors [1,2,3]. The first basic principle for AMS is the resources’ independency from neighbour systems and from its environment. This principle can be realized by dividing the manufacturing system into subsystems or clusters, and modules with standardized interfaces. The second principle of AMS is the given freedom or ability to control itself, which requires the decentralization of the control system according to the granularity of the subsystems and modules [1,2]. Implementing AMS means that, the main objective of the manufacturing system is split into many local agents, and this overcomes the problems of complexity (i.e. large volume of data) and uncertainty. The reasons behind this are as follows: the co-ordination in the manufacturing system is obtained through the intelligence of the agents; large volume of data is distributed among

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