Thomas P. Cullinane

Locating an undesirable facility with a minimax criterion

Abstract The problem considered in this paper involves the location of an undesirable facility such that the maximum weighted inverse square distance from the facility to n given points is minimized. The region in which the facility is to be located is bounded and contains the n points with which the facility to be located will interact. Applications can include siting an undesirable facility that produces some form of pollutant such as radiation, noise and some gases. Any problem that involves the location of a facility that emits pollutants whose concentrations follow the inverse square law is a candidate for the use of this work. A mathematical programming algorithm is developed for the situation in which the location problem involves a convex polygonal region. An interactive computer graphics approach is described for the case when the location problem involves a general region.

Interactive simulation modeling of automated storage retrieval systems

Owing to the complexity and enormous cost involved in Automated Material Handling Systems, there is a growing need to use computer simulation in both the physical system and control software design of such systems. Simulation models can be developed to test not only the final system configuration, but also each installation phase. This paper describes the development of an interactive and flexible simulation software for Automated Storage/Retrieval Systems( AS/RS) of the Miniload variety. A modular approach is taken in the development of the simulation software so that the user, through an interactive capability to model an menu, has the AS/RS by selecting a combination of modules that define the AS/RS. The user then enters the values of the system variables specified for each module. This user-defined simulation model is translated into a simulation language source code and then executed.

A simulation-optimisation approach for reconfigurable inventory space planning in remanufacturing facilities

Although remanufacturing facilities are becoming increasingly vital components in some supply chains, significant variability over time in returned product volumes, reusable part yields, and refurbished item demand can result in significant variability in storage requirements over time. In response, manufacturers can implement reconfigurable inventory systems to accommodate off-setting swings in storage needs between types of components and processing activities, including temporary external storage. A Monte Carlo (MC) simulation-optimisation approach has first been developed to emulate a generalised remanufacturing facility with random receiving patterns, component yields, and refurbished demand. Then, a multi-dimensional golden section search algorithm is implemented to identify optimal storage capacities and reconfiguration decisions in each time period that minimise long-term expected total cost. In pilot applications, improvements over non-reconfigurable systems range from 9% to 33% reductions in total storage space costs.

A heuristic approach to the single facility maximin location problem

The problem of determining the optimum location for a single undesirable machine within an existing plant layout is considered. The degree of undesirability between an existing machine or worker and the new machine is reflected through a weighting factor. The problem is defined to be the selection of a location witbin a convex region that maximizes the minimum weighted Euclidean distance with respect to all the existing facilities. A model is formulated and an algorithm developed. As the number of existing facilities increases, however, the computation time increases substantially. A heuristic approach hased on partial enumeration is described. This approach makes it possible to study problems that involve a large number of existing facilities without sacrificing the level of accuracy. The two approaches, exact and heuristic, are compared with respect to their computational efficiency. An example is solved using both approaches.

Understanding facilities design parameters for a remanufacturing system

Remanufacturing is rapidly becoming a very important element in the economies of the world. Products such as washing machines, clothes driers, automobile parts, cell phones and a wide range of consumer durable goods are being reclaimed and sent through processes that restore these products to levels of operating performance that are as good or better than their new product performance. The operations involved in the remanufacturing process add several new dimensions to the work that must be performed. Disassembly is an operation that rarely appears on the operations chart of a typical production facility. The inspection and test functions in remanufacturing most often involve several more tasks than those involved in the first time manufacturing cycle. A close evaluation of most any remanufacturing operation reveals several points in the process in which parts must be cleaned, tested and stored. Although several researchers have focused their work on optimizing the disassembly function and the inspection, test and store functions, very little research has been devoted to studying the impact of the facilities design on the effectiveness of the remanufacturing process. The purpose of this paper will be to delineate the differences between first time manufacturing operations and remanufacturing operations for durable goods and to identify the features of the facilities design that must be considered if the remanufacturing operations are to be effective.

Economic analysis of CNT lithium-ion battery manufacturing

Development of safe, economically competitive, and environmentally responsible nano-enabled products is desirable to avoid unintended consequences. Given the environmental health and safety uncertainties associated with nanomaterials, additional precautions for exposure prevention may be required, although not regulated. Companies working with engineered nanomaterials may want to understand decision tradeoffs for the costs associated with increased levels of occupational safety and potential environmental impacts. Recent advances in nanotechnology have resulted in the development of advanced lithium nickel manganese cobalt (NMC) oxide batteries enhanced with multiwall carbon nanotubes (MWCNT). These batteries have a much greater energy density and product life than traditional lithium-ion batteries. A stochastic process-based cost model (PBCM) is developed to investigate the cost drivers for manufacture of MWCNT NMC batteries targeted for satellite and computer applications. Various levels of occupational safety protection (low, medium and high assumed) are analyzed to determine their effect on total manufacturing cost. The results show that MWCNT cost has the highest impact on total unit cost for production of satellite batteries, whereas cycle time has the highest impact on the unit cost of computer batteries. The mixing step contributes the most to the total unit cost for both satellite and computer MWCNT NMC lithium-ion batteries due to the inclusion of MWCNT costs in the mixing step. The process-based cost model developed in this work not only offers estimation of the economic drivers associated with the MWCNT NMC battery manufacturing, but also allows consideration of strategies to reduce costs. Results contribute to safer manufacturing practices for CNT lithium-ion batteries for low and high production volume applications (satellites and portable computers, respectively).

A fuzzy cost-benefit function to select economical products for processing in a closed-loop supply chain

The cost-benefit analysis of data associated with re-processing of used products often involves the uncertainty feature of cash-flow modeling. The data is not objective because of uncertainties in supply, quality and disassembly times of used products. Hence, decision-makers must rely on “fuzzy” data for analysis. The same parties that are involved in the forward supply chain often carry out the collection and re-processing of used products. It is therefore important that the cost-benefit analysis takes the data of both new products and used products into account. In this paper, a fuzzy cost-benefit function is proposed that is used to perform a multi-criteria economic analysis to select the most economical products to process in a closed-loop supply chain. Application of the function is detailed through an illustrative example.

Economic justification of technology-based investments

This paper examines a range of problems associated with justifying investments in Manufacturing Technology and Information Technology. The appraisal of high technology projects is rather complicated in that the true costs and benefits of such strategic investments are hard to capture with conventional methods of economic decision making. This paper reviews the financial criteria currently used in practice and pinpoints why these criteria might be misleading. It is demonstrated in the paper that qualitative factors very often are the most influential factors to be considered when attempting to justify alternative investments that are environmentally responsible.

Economic Justification: Research Concerns

Economic justification of automated material handling and manufacturing systems is a frequently encountered barrier to the implementation of these systems. The purpose of this chapter is to describe the economic justification problem and to outline where current practices are inadequate. A discussion of some of the efforts being made to develop improved justification practices is presented. Individual efforts are described in terms of the issues they address and the progress they are making.