Demand planning importance

Step 3 Demand Planning The third step is one of the most important, and refers to the alignment of the demand figures that will be used by all departments for analyzing capacity availability and operational impacts, and consists of three elements ... 

Foremost we hope - and believe - that chemoinformatics will become of increasing importance in the teaching of chemistry. The instruments and methods that are used in chemistry will continue to swamp us with data and we have to manage these data to increase our chemical knowledge. We have to understand more deeply, and exploit, the results of our experiments. Concomitantly, demands on the properties of the compounds that are produced by the chemical and pharmaceutical industries will continue to rise. We will need materials that are better we need them to be more selective, have fewer undesirable properties, able to be broken down easily in the environment without producing toxic by-products, and so on. This asks for more insight into the relationships between chemical structures and their properties. Furthermore, we have to plan and perform fewer and more efficient experiments. 

It is therefore essential that a planned maintenance program be established, which can encompass all (or elements of) the different maintenance methods of establishing the frequency and/or work to be carried out. This programming requires skills that, in most instances, can have only been gained by experience in the field of maintenance and operation. Operation must play an important part in the programming. If the planned maintenance program is prepared without due consideration of the demands placed on the operation element, the program would probably collapse when the plant s equipment could not be released (i.e. switched off) when the maintenance technician arrived at the plant to carry out his duties indicated on his work docket. 

The death of old products, the birth of new ones, changing demands, and the need to compose the optimal hierarchical production plan with an optimal use of the equipment and the shortest possible total production time make the timing of production more important than plant design. The use of rigorous optimization techniques can be most profitable at production planning and scheduling of existing batch plants, especially multipurpose plants. 

Even in the absence of formal binding international implementation mechanisms for the Kyoto accord, we are seeing many businesses begin to factor greenhouse gas emission considerations into their business plans. It has simply become a good business decision and it serves customer demand. This is a profoundly important development, and nuclear power is uniquely positioned to play in this game. 

Section 6.2 introduces the most important concepts in the description of random demand. Section 6.3 deals with random service, which results from random demand and production planning. Section 6.4 discusses the optimal planning of the production given specified random demands and known stock levels. Section 6.5 illustrates the theory by a few examples of the results applied to case studies. 

Up to this point, it is assumed that prices are deterministic, which is true for contract demand and procurement but is not necessarily true for spot demand and procurement prices. Therefore, an important value chain planning requirement is the consideration of uncertain prices and price scenarios. Now, uncertain spot demand prices are under consideration and it is illustrated how price uncertainty can be integrated into the model in order to reach robust planning solutions. 

Table 7.6 shows the solution of the refineries network using the SAA scheme with N = 2000 and N = 20000 where the proposed model required 790CPUs to converge to the optimal solution. In addition to the master production plan devised for each refinery, the solution proposed the amounts of each intermediate stream to be exchanged between the different processes in the refineries. The formulation considered the uncertainty in the imported crude oil prices, petroleum product prices and demand. The three refineries collaborate to satisfy a given local market demand where the model provides the production and blending level targets for the individual sites. The annual production cost across the facilities was found to be 6 650 868. 

---