Capacity investment

Direct type, hatch operation Laboratory drying capacities, investment and operating costs are high. Long drying times ments under Pastes and Sludges... 

Fig. 5 Installed capacity sequence according to the stepwise capacity investment strategy...

Membrane cell plants show considerable capital cost advantages against diaphragm cell plants for all capacities. Investment costs for a membrane plant are 15-20% lower than the diaphragm cell plants. Production cost comparison shows that the membrane cell plant has a 10-15% lower net production cost per ton NaOH (72) (79). ... 

The return on capital calculation indicates whether or not a project is economically worthwhile. To calculate the return, assumptions must be made about the most probable product prices, the production outlay, the plant loading (actual production/nom-inal capacity), investment costs, etc. Time will see whether these assumptions are correct. The impact of these uncertainties on the cost effectiveness of the project can be quantified by using the following variables. 

Taylor, T. A. and E. L. Plambeck. 2003. Supply chain relationships and contracts the impact of repeated interaction on capacity investment and procurement. Working paper, Columbia University. 

Van Mieghem, J.A. 1998. Capacity Investment under Demand Uncertainty Coordination and the Option Value of Subcontracting. Submitted to Management Science. 

There are numerous papers that assume that demand is a Poisson process. One important early one is Li [97], who studied price and production problems with capacity investment at the beginning of the horizon. Given an initial production capacity, the demand and production rates are Poisson counting processes if there is demand in excess of production, sales are lost. Li shows that the optimal production policy under a single fixed price is a barrier or threshold policy, where production is optimal if inventory is below a certain value. Further, he characterizes the optimal policy when price is dynamic over time, and he shows that the stochastic price is always higher than the deterministic price. In extensions, he considers the case with production learning effects that is, the production rate over time becomes closer to the ideal capacity. 

A few papers that consider pricing and production decisions have also incorporated capacity investment decisions as well. For instance, Li [97] studies the short-term strategies (price) as well as long-term decisions (capacity) where cumulative production and demand are both Poisson processes. 

In Maccini [101], the author examines the long and short run pricing and inventory decisions where capacity investments can be made. Maccini assumes that expected sales have the following functional form,... 

Van Mieghem and Dada [154] focus on a single-period, two-stage process with an initial decision, e.g. production decision, followed by a realization of demand, followed by another decision, e.g. pricing decision they also consider the capacity investment decision. After the capacity is determined, production is limited, so excess sales are lost. They show how to solve this problem, and they also consider the impact of competition. They find that conditions dictate whether price postponement or production postponement is more valuable to a firm. Specifically they show that the former is likely to be more valuable if demand variability, marginal production, and holding costs are low. 

Equations (11)-(13) are total production carbon emission (PCOE) caused by the different capacity investment strategy (i.e., technology) in the closed-loop supply chain. Equation (14) represents total installation carbon emission (BCOE) of all PUs and RUs. Equations (15)-(17) are the total transportation carbon emission (TCOE) of FL and RL. 

The model presented earlier assumes steady-state conditions and provides a snapshot of the SC operation. In this section, we describe a more general formulation that considers a varying demand over time. The model includes several time periods, in each of which it is possible to take decisions regarding the SC structure. Hence, the capacity of the network can be modified over time in order to follow a predefined demand pattern, and we must find the optimal timing of capacity investments. In addition, we consider that the capacities of the plants are not fixed but rather optimized along with the plant locations. Similarly, as in the previous case, the model comprises three main blocks of equations that are next described in detail. 

The decision variables involved in our problem can be partitioned into two different sets, namely the strategic and the operational decisions. The strategic decisions reflect the decisions that must be made immediately (here-and-now) in the face of significant uncertainty and they include product selection (binary variables), allocation of products to production sites (binary variables), capacity investment decisions for the selected production sites (binary variables). 

Variability comes in many forms. It includes fluctuations in the amoxmt of work and inconsisfency in performing individual operations. An operation that becomes subject to extreme workload changes will likely have poor execution of individual operations from a variety of causes. An example is fhe need to do things in a hurry and having to throw untrained staff af fhe fask. Having to deal with volume fluctuation also adds extra operating expense, capacity investment, and inventory. 

Chakravarty and Zhang (2007) discuss a capacity exchange scenario between two firms and establish how capacity price may be determined, and how a side payment maybe used to coordinate the capacity exchange decisions. They also study a scenario where the firms capacity investment decisions are made individually and exchange decisions are made as in a centralized system. 

Chakravarty, A., Zhang, J. (2007). Lateral capacity exchange and its impact on capacity investment decisions. Naval Research Logistics, 54, 632-644. 

The U.S. chemical industry s long-held cost advantage of olefin-based products will shift to Middle East by 2008. This prospect has already resulted in a shift of new capacity investment by many U.S. producers of these products to overseas locations. While the new Middle East production is targeted to be sold into growing Asian markets, the net effect will be to displace Western-made products. 

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