Development of long-range planning for a chemical plant

We have formulated a model using fuzzy linear programming. The research data taken from an oil refinery was used and it was proved that by using the fuzzy linear programming we could significantly minimize the waste gas flow let in the atmosphere.

The productivity of chemical plants depends greatly on their production schedules. But the production schedule is mainly dependent on production time. So the scheduling of production time is particularly important in chemical plants. Chemical plants can be divided into two categories from the viewpoints of their production schedule, they are 1, Multiproduct chemical plants and 2, Multipurpose chemical plants. Here we model and study only production in multi purpose chemical plants.

In multipurpose chemical plants each operate for multiple products carried out with their own distinct equipments model sequences through the chemical plants. But the production time, period of production schedules of multipurpose chemical plants is more complicated, because the time period of production may vary, hence the time period of production scheduling is an uncertainty. As the model is a complicated one and uncertainty of both time and productivity prevails we are justified in adopting fuzzy set theory in general and fuzzy linear programming in particular in scheduling of the chemical plants.

The acceptable production flexibility and acceptable production time are determined by fuzzy set theory based on equipment models. By this approach we maximize the flexibility of production and minimize the production time.

Chemicals include raw materials, intermediates and products that may be purchased from and or sold to different markets. The main decision problem is the selection of process from among competing technologies and subsequent timing of process expansions. Also it is important to determine the optimal production levels for the installed process. The decision maker would like to maximize the net present value of the project over a long-range horizon consisting of a finite number of time periods. The net present value dependent on demands of chemicals, investments and operating cost of the processes, material costs, product prices, product demands and market demands. The demands of chemicals material cost etc., can vary from time to time. So we consider these as uncertainties and use fuzzy linear programming techniques and obtain a model and study the long range planning process for the chemical industries with a view to maximize the net present value of the project. By this method, we are able to overcome the usual problem viz., the inability to predict tight bounds.