Flexible Manufacturing Systems (FMS) are distinguished by the use of computer control. This enables FMS to reconfigure very rapidly to produce multiple part types which practically eliminates setup time.

FMS’s are adopted in the manufacturing sector on account of additional advantages like high quality, low inventory costs and low labour costs. In this article, I have discussed the possible Operations and Scheduling problems of FMS as follows:

Preproduction Setup And Production Operation

To carry out a complete setup, the FMS user should solve following problems:

1) Part type selection – The part types to be manufactured in the FMS out of the total production requirement of the industry.

2) Machine grouping – Partition the machines in the FMS so that machines in a group can perform the same operations.

3) Production Ratio – Determine the ratio of the parts selected to be manufactured in FMS.

4) Loading – Simultaneously allocate operation of the part types and corresponding tools of the machine groups.

The major constraint for the above mentioned problem is capacity of each machine tool. Stecke’s (1983) methodology suggests objectives to be optimized during the loading phase which are stated below:

• Balance the assigned machine processing times.
• Minimize the number of movements from machine to machine.
• Balance the workload per machine for a system of groups of pooled machines of equal size.
• Unbalance the workload for each machine when the pooled group sizes are unequal in order to obtain maximum production rate.
• Maximize the sum of operation priorities.

I.J. Chen and C.H. Chug’s (1991) finding was that FMS is not superior to job shop if the routing flexibility is not utilized.

K. Shanker and Tzen (1985) proposed a Mathematical Programming Approach to solve part selection problem for random FMS. They considered two objectives:

1) Balancing the workload – proposed essentially a greedy heuristic which attempts to allocate to the most lightly loaded machine the longest operation first.

2) Balancing the workload and minimizing the number of late jobs – same heuristic is modified to include the overdue jobs with the highest priority.

R. Jaikumar and L.N. Van Wassenhove (1989) proposed a Hierarchical Planning and scheduling decomposition of FMS. In first level aggregate production model is used, the essential constraints are the demand for parts and machine capacity. Second level objective is to minimize tool changeover. Production requirements and tool and machine allocation are determined in levels one and two. In the third level determine a feasible schedule that will fulfill the buffer requirements and material handling constraints.

S.M. Lee and H. Jung (1989) formulated a part selection and allocating problem using goal programming under Multiple-Criteria Decision Making Approach. They considered the goals of meeting production requirements, balancing of machine utilization and minimization of throughput time of parts.

J.A. Buzacott and J.G. Shanthikumar (1980) under Heuristics Oriented Approach considered the control of FMS as a hierarchical problem:

1) Pre-release phase – the parts which are to be manufactured are decided.

2) Input or release control – the sequence and timing of the release of jobs to the system is decided.

3) Operational control level – the movement of parts between the machines is decided.

Their relatively simple models stress the importance of balancing the machine loads and the advantage of diversity in job routing.

FMS Scheduling Problem

An approach to this problem is to decompose it into – allocation of the job to the machines in the routings and time bound sequencing of the jobs. A novel feature suggested by Hutchison (1989) is to use measure of flexibility i.e. probability of an alternate machine option for any operation.

J. Kimemia and S.B. Gershwin (1983) presented a closed loop hierarchical formulation of FMS scheduling problem under Control Theoretic Approach. A FMS is considered where parts are manufactured to meet a certain demand which could be varying over time. It would be best to produce exactly at the same rate as demand; but this cannot be done on account of the failure of machines. Stochastic machine failures are considered which are smoothed by providing buffers of the parts. The heart of this control theoretic scheduling policy is to maintain a steady safety buffer of the parts produced in FMS.

S. Jain (1989) described the development of a scheduling system which communicates on-line with the factory control system and generates schedules in real-time. The scheduling decisions are based on the expertise of an experienced scheduler. With this concept the job can be started at the latest possible time. Conflicts can be resolved by shifting individual jobs in the schedule forward or backward. The system reacts interactively with the user and permits solicitation of more information by the user or changing of the schedule.

Conclusion

FMS control problems are very complex and difficult. Rather than attempting to get the optimum solutions of problem formulations, research should be done on interactive scheduling and control of FMS where there is human input in the loop. It is time to move on to further developing comprehensive control schemes which take care of the complex interaction of the multiple resources in FMS such as – transporters, CNC machines, robots, tools, etc.

References

• I.J. Chen and C.H. Chung, “Effects of loading and routing decisions on performance of Flexible Manufacturing Systems”, International Journal of Production Research, 1991.
• J. Hutchison, K. Leong, D. Snyder and F. Ward, “Scheduling for random job shop Flexible Manufacturing Systems”, Proceedings of the third ORSA/TIMS Conference on Flexible Manufacturing Systems, 1989.
• R. Jaikumar and L.N. Van Wassenhove, “A production planning framework for Flexible Manufacturing Systems”, Journal of Manufacturing Operations Management, 1989.
• S. Jain, K. Barber and D. Osterfled, “Expert simulation for on-line scheduling”, Proceedings of the 1989 Winter Simulation Conference.
• J. Kimemia and S.B. Gershwin, “Flow optimization in Flexible Manufacturing Systems”, International Journal of Production Research, 1985.
• S.M. Lee and H. Jung, “A multi-objective production planning model in a Flexible Manufacturing environment”, International journal of Production Research, 1989.
• K. Shanker and S. Rajamarthandan, “Loading problem in FMS: part movement minimization”, Proceedings of the Third ORSA/TIMS Conference on Flexible Manufacturing Systems, 1989.
• C.B. Basnet and J.H. Mize, “An object-oriented framework for operating Flexible Manufacturing Systems”, International Conference on Object-Oriented Manufacturing Systems, Canada, 1992.
• J.A. Buzacott and J.G. Shanthikumar, “Models for understanding Flexible Manufacturing Systems”, AIIE Transactions, 1980.