Industrial Scheduling Problem

An industrial scheduling problem is presented here to illustrate the concepts discussed in this chapter. The industrial problem presented here is from a resin manufacturing plant and it involves optimizing the production schedule in order to enhance the manufacturing process performance. All production in this plant is in batch mode and three kinds of resins are produced. 

The main bottleneck of this plant is the flaker belt. Since there is only one flaker belt, the batch which has come to specifications might be kept inside the reactor depending on the batches competing for the flaker belt. Therefore the major cost associated with flaking is this tied up reactor time. Some of the formulas are less stable than others, therefore hold times for these formulas are minimized and the first priority is given to them. Making solutions takes as much time as flaking but since the resin solutions bypass the flaker belt, they don t have any resource conflicts. 

In this problem the top 10 products which account for 80% of production in the resin plant are considered. 

Our problem consists of two stages in series the reactor and fiaker belt. In the first stage, there are 5 parallel reactors, whereas in the second stage there is only one fiaker belt. Since there is zero intermediate storage between these stages, the resin which is processed must remain in the reactor if the fiaker belt is busy. 

The only difference of our problem from a standard flexible fiowshop scheduling problem is the fact that our reactors in the first stage are not identical. Not aU of the products can be processed in all of the reactors. For example, hydrocarbon resins are only produced in Reactors 5 and 6, which are vertical reactors, whereas rosin resins are only produced in Reactors 1 through 4, which are horizontal reactors. This makes our problem more complex than a standard flexible fiowshop scheduling problem because we also have to consider machine eligibility. 

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The main challenge in short-term scheduling emanates from time domain representation, which eventually influences the number of binary variables and accuracy of the model. Contrary to continuous-time formulations, discrete-time formulations tend to be inaccurate and result in an explosive binary dimension. This justifies recent efforts in developing continuous-time models that are amenable to industrial size problems. 

The classical solution to a scheduling problem assumes that the required information is known at the time the schedule is generated and that this a priori scheduling remains fixed for a planning period and is implemented on the plant equipment. Although this methodology does not compensate for the many external disturbances and internal disruptions that occur in a real plant, it is still the strategy most commonly found in industrial practice. Demand fluctuations, process devia-... 

Real-life scheduling problems usually are very different from the mathematical models studied by researchers in academia and industrial research centers. It is difficult to categorize all differences between the real problems and the theoretical models, as each real-life scheduling problem has its own idiosyncrasies. Nevertheless, a number of these differences do stand out and are worth mentioning. 

Tsujimura, Y, Park, S., Chang, S., and Gen, M. (1993), An Effective Method for Solving Flow Shop Scheduling Problems with Fuzzy Processing Times, Computers and Industrial Engineering, Vol. 25, pp. 239-242. 

Siswanto, N., Essam, D., and Sarker, R. Solving the ship inventory routing and scheduling problem with undedicated compartments. Computers Industrial Engineering, 61(2) 289-299, 2011. 

F owler, J., Homg, S. and Cochran, J., 2003. A hybridized genetic algorithm to solve parallel machine scheduling problems with sequence dependent setups. International Journal of Industrial Engineering-Theory Applications and Practice, 10(3), 232-243. 

Guo, Z.X., Wong, W.K., Leung, S.Y.S., Fan, J.T. and Chan, S.F., 2006. Mathematical model and genetic optimization for the job shop scheduling problem in a mixed- and multi-product assembly environment A case study based on the apparel industry. Computers and Industrial Engineering, 50(3), 202-219. 

Kondakci, S. and Gupta, R., 1991. An interactive approach for a dual conshaint job shop scheduling problem. Computers and Industrial Engineering, 20(3), 293-302. 

Constraint programming has been successfully applied to problem areas as diverse as DNA structure analysis, time-tabling for hospitals, and industry scheduling. It is well adapted to solving real-life problems because many application domains evoke constraint description naturally. Some examples follow ... 

Scheduling problems Examples are (1) the petroleum industry, (2) forest treatment scheduling, (3) production scheduling in the plastic industry, (4) planning the production of military and business jets. The use of constraints... 

Choi, I.C. Choi, D.S. (2002). A local search algorithm for job shop scheduling problems with alternative operations and sequence-dependent setups. Computers and Industrial Engineering, Vol. 42, pp. 43-58. 

The scheduling problem is a cmcial problem in all industrial production systems. Scheduling of production serves essential roles which can be regarded as the indicator of overall production efficiency. With the intense competition of industries, suitable methods are needed in order to maximize the efficiency of the production management system to be able to compete in the industrial market. The common scheduling problem of production is exceedingly complicated, especially... 

The scheduling problem in the chemical industry has been extensively studied and alternative methodologies and problem statements have been proposed in the literature to address the combinatorial character of this problem (Shah, 1998). However, most of the formulations presented are based on nominal parameter values without eonsidering the uncertain requirements after the operations are planned and scheduled. The uncertainty from a real environment entails a risk that is initially traduced in a cost but may lead to an unfeasible situation. 

A Decomposition Strategy for Solving Multi-Product, Multi-Purpose Scheduling Problems in the Paper Converting Industry... 

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