Object-Oriented Control Architecture For Ams Manufacturing

Introduction    

In recent past, the industrial sectors have started presenting additional inclination towards flexible automation and manufacturing. It has occurred in response to the fast changing customers' demands and raised global competition due to foreign interventions in the market. Flexible automation has become a bandwagon, more and more companies are turning their services to Flexible Manufacturing Systems, and it has become possible due to efficient and increased utilize of technological advancement in robotics and computers in industry.

Decreasing production cycle time and responding to the quick change of product designs have become the means of thriving and surviving in the competitive market for most  of the manufacturing companies. Manufacturing planning, as well as tooling, makes main contributions in the production cycle. The improvement of CNC machines has made machining time slighter than ever. Here the focus is on decreasing the time concerned in the set-ups. Thus, the design and improvement of computer aided set-up planning is essential to realize the flexible manufacturing systems in true sense. In the current past, owing to the proliferation of industrial robots and the improvement in the broad field of computers of application in different techniques to solve industrial problems, the possibility of the advanced manufacturing systems is bolstered. The flexibility in the flexible manufacturing systems can be identified in two ways: either the parts move to different workstations or the tools are moved. In the latter case a machining systems which is able of performing various operations is considered. In this condition, instead of moving jobs to the machining stations merely tools are managed to in the tool slot to minimize the tool magazine replenishments. Conversely, experience has demonstrated that the implementation of full blown flexible manufacturing systems has not, generally, given the anticipated awards. Therefore, various companies have pursued utilize of flexible cells as means to achieve to flexible automation.

Group Technology or GT is a strategy to manufacturing that assists in identifying similar parts and grouping them together in cells, obtaining advantage of their same characteristics. Group Technology has various applications in manufacturing environment; one of the significant applications of Group Technology is determined in developing Cellular Manufacturing or CM. Cellular Manufacturing deals along with operation and formation of cells via taking into account the same nature of parts, tools, machines, operations. The formation of cells causes division of large manufacturing unit in subunits along with each cell containing minimal or no interaction along with the other cells. The benefit of cellular manufacturing or CM over functional manufacturing ranges from decreases  in  setup  time,  throughput  time,  work  in  process  or WIP,  inventories  to justified flow of raw material and parts, and enhanced human relations.

In the successful implementation, one critical task of flexible cells is the development of the cells in the development of cell control system like the yield of a technique can vary quite considerably  from  less  experienced  operators  and  operator  to  operator  are  often not capable to control a plant efficiently, mostly under abnormal situations that they have never met before.

Furthermore, the control actions of a human operator are subjective, often incomprehensible and frequently prone to errors mostly while they are under stress. Conversely in the case of unusual operating conditions, their events may be potentially dangerous and there is small margin for errors. Waits in making decisions can cause disastrous results.

Hence, in modem complex plants there exist an extremely real required to help operators in their decision-making, mostly in abnormal situations in which, they are bombarded along with conflicting signals. The Computational Intelligence advent and unconventional control free operators of various of the tedious and complicated chores of controlling and monitoring a plant, assuring them quick and consistent maintain in their decision-making.

In the past twenty years or consequently, a main effort has been under manner to develop latest and unconventional control techniques such can frequently augment or replace conventional control techniques.  Various unconventional control processes have evolved, offering solutions to various complicated control problems in manufacturing and industry. This is the essence of what has been called Practical Control that is a collection of techniques that practicing engineers have determined effective and simple to utilize in the field. This is true to say that virtually all the process of unconventional control could not have been probable but for the availability of computationally high-speed and powerful computers.

Important research has been carried out in knowing and emulating human intelligence whilst, in parallel, increasing inference engines for processing human knowledge. The resultant process incorporate notions gathered from a broad range of specialization as like: neurology, operations research, psychology, conventional control theory, and communications theory and computer science.

This is the domain of Soft Computing that focuses upon stochastic, empirical, vague and relative situations, classic of the manufacturing and industrial environment. Intelligent Controllers are derivatives of Soft Computing, being characterized through their capability to found the functional relationship among their inputs and outputs from empirical data. It is a radical departure from conventional controllers that are based upon explicit functional relations. Not like their intelligent controllers, conventional counterparts can learn, make decisions and remember. The functional relationship among the inputs and outputs of an intelligent controller can be identified either.

Intelligent controllers, anything forms they may obtain, share the given properties:

• Utilize parallel distributed associative processors,
• Utilize the similar process states,
• Assure generality, and
• Able of processing and codifying vague data.

Computational Intelligence is the principal medium of intelligent control, the branch of Soft Computing.

To attain its potential, flexible automation should have robust control software that can run on a number of hardware platform and specify the following abilities.

• The software must be capable to communicate along with all devices in the cell and control cell action, minimize delays among signals and consequent actions.
• Errors in the system should be detected and handled inside strict time limits.
• The cell control software should simply adapt to dissimilar cell configurations.
• The software should be extensible to accommodate the addition of latest components to the cells.

In this section, cell control systems are represented as a means to achieving automated manufacturing systems and that embodies the ideas of object-oriented programming and design and thus has the following characteristics:

• Structured, hierarchical knowledge presentation,
• Information hiding and data encapsulation,
• Reusable and flexible code, and
• Inheritance of values.