Mario T. Tabucanon

A multicriteria approach to the selection of preventive maintenance intervals

Abstract This paper discusses the problem of determining optimal preventive-maintenance intervals for components in a production system. The maintenance planning of a paper factory is taken as a case study. The traditional approach of a single objective function for this type of a problem is described, and some of the disadvantages of taking such a single objective are discussed. The paper proposes a new model incorporating multiple criteria. For the case study, two criteria, expected costs and reliability, are taken into consideration. The MCDM method PROMETHEE is used to solve the problem. Sensitivity analysis is carried out for the variations in the subjective weights assigned to the criteria.

Decision support system for multicriteria machine selection for flexible manufacturing systems

Abstract This paper proposes an approach to the design and development of an intelligent Decision Support System (DSS) that is intended to help the selection process of alternative machines for Flexible Manufacturing Systems (FMS). The process consists of a series of steps starting with an analysis of the information and culminating in a conclusion —a selection from several available alternatives and verification of the selected alternative to solve the problem. In real decision situations, more than one criterion is present, and the problem becomes multicriteria decision making. The approach presented combines the Analytic Hierarchy Process (AHP) technique for multicriteria decision making with the rule-based technique for creating Expert Systems (ES). Such an approach allows the past experience, expressed as heuristics in ES, to be used. Moreover, this approach determines the architecture of the computer-based environment necessary for the decision support software system to be created. It includes the AHP software package (Expert Choice), Dbase III + DBMS, Expert System shell (EXSYS) and Turbo Pascal compiler (for the external procedural programs). As a result, a prototype decision support system for a fixed domain, namely a CNC turning center that is required to process a family of rotational parts, is developed. It helps the user to find the most “satisfactory” machine on the basis of several objective as well as subjective attributes.

Planning for project control through risk analysis: a petroleum pipeline-laying project

Projects that are exposed to uncertain environments can be effectively controlled with the application of risk analysis during the planning stage. The Analytic Hierarchy Process, a multiattribute decision-making technique, can be used to analyse and assess project risks which are objective or subjective in nature. Among other advantages, the process logically integrates the various elements in the planning process. The results from risk analysis and activity analysis are then used to develop a logical contingency allowance for the project through the application of probability theory. The contingency allowance is created in two parts: (a) a technical contingency, and (b) a management contingency. This provides a basis for decision making in a changing project environment. Effective control of the project is made possible by the limitation of the changes within the monetary contingency allowance for the work package concerned, and the utilization of the contingency through proper appropriation. The whole methodology is applied to a pipeline-laying project in India, and its effectiveness in project control is demonstrated.

Component part standardization: A way to reduce the life-cycle costs of products

Abstract This paper studies the effects of component part standardization on life-cycle costs. Three possible situations for component standardization are discussed. A summary is presented of various costs in different phases of the product life cycle and how they are shared among the manufacturer, user, and society. Then, we explain how the component standardization reduces the costs of different phases of the product life cycle. Finally, we point out some of the possible disadvantages of component standardization.

A multiple-criteria approach to machine selection for flexible manufacturing systems

Abstract This paper describes a visual interactive decision support framework designed to aid decision makers in selecting the most appropriate machines for a flexible manufacturing system (FMS). The framework can be used in the preinvestment stage of the planning process, after a decision has been made, in principle, to build an FMS . The framework mainly consists of two parts. The first part is called the prescreening stage , which narrows down all possible configurations by using the analytic hierarchy process (AHP). The second part uses a goal programming (GP) model to find out the satisfactory candidate from the remaining shortlisted configuration. After applying the GP model, AH P is used again for sensitivity analysis. This approach helps managers explore and evaluate costs and benefits of various scenarios for each configuration separately by experimenting with different types of machines and degrees of flexibility of the system.

Petroleum pipeline construction planning: a conceptual framework

A cross-country pipeline construction project is exposed to an uncertain environment due to its enormous size (physical, manpower requirement and financial value), complexity in design technology and involvement of external factors. These uncertainties can lead to several changes in project scope during the process of project execution. Unless the changes are properly controlled, the time, cost and quality goals of the project may never be achieved. A methodology is proposed for project control through risk analysis, contingency allocation and hierarchical planning models. Risk analysis is carried out through the analytic hierarchy process (AHP) due to the subjective nature of risks in construction projects. The results of risk analysis are used to determine the logical contingency for project control with the application of probability theory. Ultimate project control is carried out by hierarchical planning model which enables decision makers to take vital decisions during the changing environment of the construction period. Goal programming (GP), a multiple criteria decision-making technique, is proposed for model formulation because of its flexibility and priority-base structure. The project is planned hierarchically in three levels—project, work package and activity. GP is applied separately at each level. Decision variables of each model are different planning parameters of the project. In this study, models are formulated from the owners perspective and its effectiveness in project control is demonstrated.

The harvest of microalgae from the effluent of a sewage fed high rate stabilization pond by Tilapia nilotica: Part 2: Studies of the fish ponds

Abstract Tilapia nilotica grew well in the fish ponds fed with algal laden high rate stabilization pond effluent, but ceased to grow after 3 months in the 4 m3 concrete ponds, irrespective of stocking density or mean pond algal concentration. Relationships between fish growth and stocking density were established, which may be of use in further studies on waste recycling systems involving Tilapia. The mean weight of individual fish fell as the stocking density was increased but the final yield or weight of the fish population increased. A fish stocking density of 10/m3 may be sufficient to produce a high fish yield, although composed of small individual fish, suitable for processing into high protein animal feed. Extrapolated yields approaching 20 tons/ha/year were obtained in the 4 m3 concrete pond system based on 3 month growing periods, but evidence was presented which indicates that similar yields may be obtainable in larger, earth ponds with a single fish crop/year. A linear relationship was established between fish yields and mean phytoplankton concentration in the fish ponds. A concentration of 70 mg/l may be high enough to produce good fish growth, since higher concentrations would lead to zero pond dissolved oxygen concentrations in the early morning hours. Since phytoplankton, including blue green and euglenoid algae, were the dominant biota in the ponds and in fish guts, the fish obviously filtered the microalgae from the water and used them as food. Crude food conversion ratios based on phytoplankton added and retained in the fish ponds were 6.2 and 2.5 at maximum fish yields, respectively. Since the lower value is similar to that obtained with some high protein supplementary feeds, the high nutritional value of waste grown microalgae was demonstrated. The efficiency of fish production/unit phytoplankton biomass increased as the detention time and therefore the mean pond phytoplankton concentration was reduced; however, maximum efficiency would require large areas of land to obtain significant fish yields, since fish growth was directly correlated with mean pond phytoplankton concentration. The key to increasing fish production in the tropics with minimal energy inputs may well be via waste grown microalgae.

Batch-model assembly line balancing: A multiattribute decision making approach

Traditionally, assembly line balancing involves determining the number of workstations using a single criterion method like balance delay, production cost or number of workstations minimization under certain constraints. The cycle time, determined from the demand of the product, is taken as an input parameter. This approach may not be well-suited for a batch-model assembly line under frequent changeover situation because of the desirability to reduce changeover time. In this paper, a multiattribute-based approach is developed to determine the number of workstations. At first, a set of feasible number of workstations which are balanced for each product model are generated. A procedure is then developed to compute the changeover time for each configuration (number of workstation), and finally, a multiattribute evaluation model is developed to select the number of workstations considering production rate, variety, minimum distance moved, division of labor and quality using the analytic hierarchy process and simulation. The methodology is then applied to a real-life batch-model assembly line for printing calculators.

Multiple criteria approach for solving feeder assignment and assembly sequence problem in PCB assembly

The feeder assignment and assembly sequence problem in printed circuit board (PCB) assembly with the twin objectives of minimizing magazine travel time and minimizing board travel time is presented in this study. The problem uses Dynamic Pick-and-Place (DPP) model where robot arm, board and magazine move together with different speeds based on relative coordinates between consecutive assembled points. The difficulty of the problem is that the feeder assignment depends on assembly sequence and vice versa. A new approach is proposed to improve the existing approaches. The trade-off between two strategies, assembly by area and assembly by component types, can give better results. The numerical experiments proved the efficiency of the new algorithm.

Bicriterion linear programming

Abstract Basically leaning on the concept of “best” compromise, the technique seeks the optimal solution by fair relaxations of the objectives commensurate with their degrees of importance until the optimum feasible compromise is reached. The concept is made operational by deriving a linear constraint (referred to as the compromise constraint) to be added into the original set. An offspring of both objective functions, the compromise constraint cuts the original feasible region and forces both objectives to settle on a common point along this added restriction. The resulting singular equivalent of the bicriterion problem optimizes any one of the two objective functions and their equivalent sum (referred to as the supergoal) subject to the new set of constraints. Post optimality analysis is employed to minimize the computational effort usually done by a computer. A very attractive feature of this new practical technique is its ability to search for the optimum in any point in the feasible region, even other than the vertices of the convex set.