David Ben-Arieh

Activity-based cost management for design and development stage

Abstract The fierce global competition in the international markets forces manufacturers to compete in quality, cost, and the time to market aspects of their products. Knowing the cost of the manufactured components is essential for efficient operation and competitive production. The current evolution of competitive manufacturing requires a shorter market life span of products—emphasizing the design and development phase of the product life cycle. Thus, it has become more important to analyze the cost of the design and development phase accurately. Activity-based costing (ABC) has become a mature cost estimation and accounting methodology. Using ABC for cost estimation of manufactured parts is being practiced today with acceptable rate of success. Cost estimation of the design activity on the other hand, has been nebulous and hard to implement. This paper presents a methodology of using ABC to evaluate the cost of the design and development activity for machined parts. The methodology is demonstrated on a sample part being produced in a controlled manufacturing facility.

Multi-criteria group consensus under linear cost opinion elasticity

Consensus is a pivotal concept in group decision making. Many times, such a consensus is achieved by the experts shifting their opinion towards a point of mutual consent. Such a shift in many cases is the result of laborious negotiations, which escalates the cost of reaching the consensus. Moreover, many times the group decision is multi-criteria oriented in which the experts need to agree on each criterion separately. This paper describes three problems where experts of unequal importance and with a linear cost of changing their opinion (opinion elasticity) consider a single and a multi-criteria decision consensus. These problems achieve a minimum cost consensus without a budget limit. It turns out that the optimal consensus point is at the median opinion for rectilinear cost function and at the weighted average opinion for squared geometric distance calculations. Linear-time algorithms are presented for all cost consensus problems with no budget limits. Proofs, computational complexity and examples are provided for these algorithms.

Minimum Cost Consensus With Quadratic Cost Functions

Group consensus is an important method for making business decisions. In this paper, the consensus process is defined as a dynamic and interactive group decision process, which is coordinated by a moderator who helps the experts to gradually move their opinions closer to each other. This paper describes the importance of group consensus and the need to minimize the cost of this process. Furthermore, this paper describes the costs associated with decision making using group consensus and then describes three methods of reaching consensus assuming quadratic costs for a single-criterion decision problem. The first method finds the group opinion (consensus) that yields the minimum cost of reaching throughout the group. The second method finds the opinion with the minimum cost of the consensus provided that all experts must be within a given distance of the group opinion. The last method finds the maximum number of experts that can fit within the consensus, given a specified budget constraint.

Annealing method for PCB assembly scheduling on two sequential machines

Abstract Modern electronic printed circuit board assembly (PCB) typically employs specialized component insertion machines, in a flow-shop-type facility. Since the mix of boards on production utilizes more component types than the machines contain, there is a sequence-dependent set up time between the board types. The setup time is very significant relative to the fast insertion operation. This paper demonstrates the simulated annealing approach as a tool for sequencing the boards on two sequential insertion machines, in order to minimize the average flow time of the boards. This approach is experimented on a real industrial problem and its results and computation times are presented.

Quantifying data for group technology with weighted fuzzy features

SUMMARY The high potential of using group technology in manufacturing has attracted the interest of both practitioners and researchers. Group technology is based on clustering parts which have similar features. Very often it is very hard to quantify successfully data regarding these features. This is because in many real applications features are fuzzy. This paper identifies two types of fuzzy features: qualitative features, and quantitative ones with subjective meaning. The paper presents a methodology for quantifying the data that refer to the fuzzy features. The proposed methodology deals with crisp and fuzzy data in a unified manner. Finally, some clustering approaches which process the quantified features are also discussed

The role of human factors in telehealth

The purpose of this article is to provide an overview of the field of human factors (HFs) and its role in telehealth. We discuss HF concepts and methodologies that affect the design, implementation, and evaluation of telehealth applications and provide examples from numerous application areas that highlight the significance of HF principles and methodologies. We also provide recommendations for inclusion of HFs in telehealth system design and evaluation, and discuss resulting implications for system designers, practitioners, vendors, and policy makers.

Linguistic group decision-making: opinion aggregation and measures of consensus

Group decision-making is a crucial activity, necessary in many aspects of our civilization. In many cases, due to inherent complexity, experts cannot express their opinion or preferences using exact numbers, thus resorting to a qualitative preference such as linguistic labels. Another complicating factor is the fact that very seldom all individuals in a group share the same opinion about the alternatives. This creates the need to aggregate all the differing individual opinions into a group opinion. Moreover, it is desirable to be able to assess the level of agreement among the experts; termed consensus. This paper presents a methodology for aggregating experts’ judgements, presented as linguistic labels, into a group opinion with a measure of the group consensus. The aggregation model allows weighted experts to express a degree of optimism or upward bias in their opinions. Then the paper presents two models of calculating the consensus based on the individual expert opinions and the group aggregated opinion.

Solving the multiple platforms configuration problem

The focus of manufacturing has been shifting from mass production to mass customization and producers are seeking ways to reduce production costs, still offering a competitive basket of products. One approach for implementing mass customization is to develop or produce products based on platform architecture. Variant products make use of the product platform as the starting point and then add or remove components to change features of the base product. This allows the manufacturer to offer the variety of products that meet market demands without developing each product independently. In this paper, we propose multiple platforms for the production of a given product family while minimizing the overall production cost. The methodology considers the demand for each product variant, with the decision variables as the optimal number of platforms, optimal configuration of each platform, and assignment of the products to the platforms. The problem is formulated as a mixed integer program, and both the optimal formulation and an evolutionary strategy based on Genetic Algorithm are presented. The approach is illustrated with an example from a family of cordless drills.

Computer-aided process planning for assembly: generation of assembly operations sequence

Process planning for assembly requires a computerized representation and analysis of assembled products. In order to recommend a good sequence of assembly operations, the process planner needs to generate all such feasible sequences. This paper presents a methodology to consistently generate all feasible asssembly sequences with consideration for the various combinations of subassembly operations. The methodology is demonstrated on a real product. A practical method to reduce the number of feasible combinations generated is also demonstrated.

Part assignment to electronic insertion machines: two machine case

SUMMARY Modern electronic circuit board production typically uses computerized insertion machines to insert electronic components into circuit boards in a flow shop type of production line. This paper studies the problem of assigning components to insertion machines with the aim of maximizing output. The paper initially examines the two machine assignment case, identifying requirements sufficient to ensure an optimal solution for two technological scenarios. Moreover, it is noted that the sequencing issue of different board types in a production cycle is immaterial, given large machine capacity. Solution procedures for this components assignment problem are described and tested on data obtained from a real life industrial setting. The resulting solutions are within 0-5% from optimality.