Capacity Planning and Leadtime management

In this paper we discuss a framework for capacity planning and lead time management in manufacturing companies, with an emphasis on the machine shop. First we show how queueing models can be used to find approximations of the mean and the variance of manufacturing shop lead times. These quantities often serve as a basis to set a fixed planned lead time in an MRP-controlled environment. A major drawback of a fixed planned lead time is the ignorance of the correlation between actual work loads and the lead times that can be realized under a limited capacity flexibility. To overcome this problem, we develop a method that determines the earliest possible completion time of any arriving job, without sacrificing the delivery performance of any other job in the shop. This earliest completion time is then taken to be the delivery date and thereby determines a workload-dependent planned lead time. We compare this capacity planning procedure with a fixed planned lead time approach (as in MRP), with a procedure in which lead times are estimated based on the amount of work in the shop, and with a workload-oriented release procedure. Numerical experiments so far show an excellent performance of the capacity planning procedure

A Decision Support System for Ship Maintenance Capacity Planning

In this paper, the basic framework and algorithms of a decision support system are discussed, which enhance process and capacity planning at a large repair shop. The research is strongly motivated by experiences in a project carried out at a dockyard, which performs repair, overhaul and modification programs for various classes of navy ships. We outline the basic requirements placed upon order acceptance, process planning and capacity scheduling for large maintenance projects. In subsequent sections a number of procedures and algorithms to deal with these requirements, in particular a procedure for workload-based capacity planning, a database system to support process planning are developed, as well as a resource-constrained project scheduling system to support work planning at a more detailed level. The system has been designed to support decision making at the Navy Dockyard in particular, however, we believe that, due to its generic structure, it is applicable to a wide range of project-based manufacturing and maintenance environments

Incentivizing Reliable Demand Response with Customers' Uncertainties and Capacity Planning

One of the major issues with the integration of renewable energy sources into the power grid is the increased uncertainty and variability that they bring. If this uncertainty is not sufficiently addressed, it will limit the further penetration of renewables into the grid and even result in blackouts. Compared to energy storage, Demand Response (DR) has advantages to provide reserves to the load serving entities (LSEs) in a cost-effective and environmentally friendly way. DR programs work by changing customers' loads when the power grid experiences a contingency such as a mismatch between supply and demand. Uncertainties from both the customer-side and LSE-side make designing algorithms for DR a major challenge. This paper makes the following main contributions: (i) We propose DR control policies based on the optimal structures of the offline solution. (ii) A distributed algorithm is developed for implementing the control policies without efficiency loss. (iii) We further offer an enhanced policy design by allowing flexibilities into the commitment level. (iv) We perform real world trace based numerical simulations which demonstrate that the proposed algorithms can achieve near optimal social cost. Details can be found in our extended version.Comment: arXiv admin note: substantial text overlap with arXiv:1704.0453

Creating Responsive Information Systems with the Help of SSADM

In this paper, a program for a research is outlined. Firstly, the concept of responsive information systems is defined and then the notion of the capacity planning and software performance engineering is clarified. Secondly, the purpose of the proposed methodology of capacity planning, the interface to information systems analysis and development methodologies (SSADM), the advantage of knowledge-based approach is discussed. The interfaces to CASE tools more precisely to data dictionaries or repositories (IRDS) are examined in the context of a certain systems analysis and design methodology (e.g. SSADM)

Prison capacity planning

The demand pressures on the prison system are becoming unsustainable, according to this report. 2012–13 forecasts by Corrections Victoria (CV) indicate that by 2016 the male and female prison systems will not have sufficient capacity to meet increases in prisoner numbers. A 38 per cent increase in prisoner numbers over the past decade and a heavy reliance on temporary beds has resulted in the existing prison infrastructure nearing its capacity limits. Since May 2011, the male prison system has been operating close to or above 95 per cent utilisation. The number of prisoners held in police cells in 2012 has reached the highest levels since 2002. Despite the current state of the prison system, CV has been active over the past 10 years in planning for growing prisoner populations, but could improve its forecasting approach. CV’s long-term planning has included initiatives that would have alleviated the current overcrowding problems. However, the success of this planning has been compromised by delays in the construction of one prison and the funding of a new prison

Agame-theoretical approach to network capacity planning under competition

The paper discusses the dimensioning strategies of two network providers (operators) that supply channels to the same population of users in a competitive environment. Usersare assumed to compete for best service (lowest blocking probability of new request), while operators wishto maximize their profits. This setting gives rise to two interconnected, noncooperative games: a) a users game, in which the partition of primary traffic between operators is determined by the operators' channel capacities and by the users' blocking-avoidance strategy; and b) a network dimensioning game between operators in which the players alternate dimensioning decisions thatmaximize their profit rate under the current channel capacity of his/her opponent. At least for two plausible users' blocking avoidance strategies discussed in the paper, the users game will always reach some algorithmic equilibrium. In the operators' game, the player strategies are given by their numbers of deployed chanels, limited by their available infrastructure resources. If the infrastrucutre is under-dimensioned with respect to the traffic rate, the operators game willreach a Nash equilibrium when both players reach full use of their available infrastructures. Otherweise, a Nash equilibrium may also arise if both operators incur the same deployment costs. If costs are asymmetric, though, the alternating game may enter a loop. If the asymmetry is modest, both players may then try to achieve a competitive monopoly in which the opponent is forced to leave the game or operate with a loss (negative profit). However, if the asymmetry is high enough, only the player with the lower costs can force his opponent to leave the game while still holding a profitable operation. --network dimensioning,game theory,duopoly,Nash equilibrium,circuit switching,blocking probability