Showing papers in "Omega-international Journal of Management Science in 2006"

The impact of supply chain management practices on competitive advantage and organizational performance

Abstract: Effective supply chain management (SCM) has become a potentially valuable way of securing competitive advantage and improving organizational performance since competition is no longer between organizations, but among supply chains. This research conceptualizes and develops five dimensions of SCM practice (strategic supplier partnership, customer relationship, level of information sharing, quality of information sharing, and postponement) and tests the relationships between SCM practices, competitive advantage, and organizational performance. Data for the study were collected from 196 organizations and the relationships proposed in the framework were tested using structural equation modeling. The results indicate that higher levels of SCM practice can lead to enhanced competitive advantage and improved organizational performance. Also, competitive advantage can have a direct, positive impact on organizational performance.

The multiple traveling salesman problem : an overview of formulations and solution procedures

Abstract: The multiple traveling salesman problem (mTSP) is a generalization of the well-known traveling salesman problem (TSP), where more than one salesman is allowed to be used in the solution. Moreover, the characteristics of the mTSP seem more appropriate for real-life applications, and it is also possible to extend the problem to a wide variety of vehicle routing problems (VRPs) by incorporating some additional side constraints. Although there exists a wide body of the literature for the TSP and the VRP, the mTSP has not received the same amount of attention. The purpose of this survey is to review the problem and its practical applications, to highlight some formulations and to describe exact and heuristic solution procedures proposed for this problem.

Empirical research opportunities in reverse supply chains

Abstract: This study reviews the literature in reverse supply chains (RSCs) and develops 10 research propositions to be studied using empirical research methods. Businesses increasingly have to cope with product returns, mandated environmental regulations and increasing costs associated with product disposal. Through effective management of the RSC, managers can improve process efficiencies, customer service, supply chain design, product design, after-market product sales and after-sales service. Most research in RSCs has relied on case studies and optimization models. Opportunities exist to use survey-based research methods to explain current practices, predominant and critical issues, and managerial techniques used to manage the RSC.

A genetic algorithm approach to developing the multi-echelon reverse logistics network for product returns

Abstract: Traditionally, product returns have been viewed as an unavoidable cost of doing business, forfeiting any chance of cost savings. As cost pressures continue to mount in this era of economic downturns, a growing number of firms have begun to explore the possibility of managing product returns in a more cost-efficient manner. However, few studies have addressed the problem of determining the number and location of centralized return centers (i.e., reverse consolidation points) where returned products from retailers or end-customers were collected, sorted, and consolidated into a large shipment destined for manufacturers’ or distributors’ repair facilities. To fill the void in such a line of research, this paper proposes a nonlinear mixed-integer programming model and a genetic algorithm that can solve the reverse logistics problem involving product returns. The usefulness of the proposed model and algorithm was validated by its application to an illustrative example dealing with products returned from online sales.

The integration of TQM and technology/R&D management in determining quality and innovation performance

Abstract: This paper presents an empirical study which examines the co-alignment between Total Quality Management (TQM) and technology/research and development (R&D) management in predicting organizational performance in terms of quality and innovation. This study improves our understanding of the relationship between TQM and innovation based on the following two major issues. First, this study contributes to the understanding of the co-alignment between TQM and technology management along with R&D management by bridging the gap between the two areas which are often addressed in a separate fashion. Second, this study also examines the impact of the integration between TQM and technology/R&D on quality and innovation performance which have been considered as the primary sources of a competitive advantage. The empirical data was drawn from 194 Australian organizations and analyzed using the Structural Equation Modeling (SEM) technique. The findings indicate that TQM shows a strong predictive power against quality performance but no significant relationship against innovation performance. On the other hand, technology and R&D management shows a significant relationship with quality performance but at a lower level than that of TQM, and shows much stronger relationship with innovation performance. In addition, there is strong and positive correlation between TQM and technology/R&D management. The major implication of this study is that technology/R&D management is an appropriate resource to be used in harmony with TQM to enhance organizational performance, particularly innovation.

Two new robust genetic algorithms for the flowshop scheduling problem

Abstract: The flowshop scheduling problem (FSP) has been widely studied in the literature and many techniques for its solution have been proposed. Some authors have concluded that genetic algorithms are not suitable for this hard, combinatorial problem unless hybridization is used. This work proposes new genetic algorithms for solving the permutation FSP that prove to be competitive when compared to many other well known algorithms. The optimization criterion considered is the minimization of the total completion time or makespan ( C max ). We show a robust genetic algorithm and a fast hybrid implementation. These algorithms use new genetic operators, advanced techniques like hybridization with local search and an efficient population initialization as well as a new generational scheme. A complete evaluation of the different parameters and operators of the algorithms by means of a Design of Experiments approach is also given. The algorithm's effectiveness is compared against 11 other methods, including genetic algorithms, tabu search, simulated annealing and other advanced and recent techniques. For the evaluations we use Taillard's well known standard benchmark. The results show that the proposed algorithms are very effective and at the same time are easy to implement.

Contemporary maintenance management: process, framework and supporting pillars

Abstract: This paper presents a holistic framework for managing the maintenance function heretofore inundated by myriad tools, trappings, practices, and prescriptions. It begins by reviewing the concepts, state-of-art processes and standards available to help maintain today’s complex systems. It then proposes a framework in which to couch the various maintenance functions in an organization. In doing so, this paper characterizes factors that breed complexity in maintaining today’s operations. Next, it closely analyzes the strategic, tactical and operational aspects ofmaintenance and sets up a structure to help complete the tasks at each ofthese levels. The term “process” in this paper implies actions directly associated with maintenance, while “framework” embodies the supporting infrastructure. The results are clear statements of(1) the f required of enablers such as IT to abet maintenance; (2) the distinctive capabilities extended by modern maintenance engineering; and (3) the critical requirement of relationship competencies in maintenance. This work sums up decades spent in maintenance shops, engineering, standardization, and research in maintenance management. 2004 Elsevier Ltd. All rights reserved.

An analytic model for locating facilities strategically

Abstract: This paper presents a strategic solution to the facility location problem which incorporates both external and internal criteria in the decision-making process. The external components of the model are customers and their wants, competitors, and the characteristics of various locations. The internal components of the model are the critical processes in the manufacturing organization. The framework presented uses quality function deployment (QFD), analytic hierarchy process (AHP) and analytic network process (ANP). QFD matrices with interconnected rows and columns relate market segments, competitive priorities, critical processes, location attributes and various locations. AHP determines the intensity of the relationship between the row and column variables of each matrix. Finally, ANP determines the intensity of synergistic effects among column variables. The model fine-tunes and adds precision to an otherwise qualitative strategic decision process. The applicability of our proposed model is demonstrated with a case study that summarizes an intervention in which the model's framework and basic concepts were applied.

Interactive fuzzy goal programming for multi-objective transportation problems ☆

Abstract: This paper presents an interactive fuzzy goal programming approach to determine the preferred compromise solution for the multi-objective transportation problem. The proposed approach considers the imprecise nature of the input data by implementing the minimum operator and also assumes that each objective function has a fuzzy goal. The approach focuses on minimizing the worst upper bound to obtain an efficient solution which is close to the best lower bound of each objective function. The solution procedure controls the search direction via updating both the membership values and the aspiration levels. An important characteristic of the approach is that the decision maker's role is concentrated only in evaluating the efficient solution to limit the influences of his/her incomplete knowledge about the problem domain. In addition, the proposed approach can be applied to solve other multi-objective decision making problems. The performance of this solution approach is evaluated by comparing its results with that of the two existing methods in the literature.

Remanufacturing of mobile phones—capacity, program and facility adaptation planning

Abstract: Successful remanufacturing of mobile phones must meet the challenges of continuously falling prices for new phone models, short life cycles, disassembly of unfriendly designs and prohibiting transport, labor and machining costs in high-wage countries. A generic remanufacturing plan for mobile phones is developed. For the planning of remanufacturing capacities and production programs, a linear optimization model is introduced. To support the planner in the periodic adaptation of an existing remanufacturing facility under quickly changing product, process, and market constraints, discrete-event simulation is applied. Uncertainties regarding quantity and conditions of mobile phones, reliability of capacities, processing times, and demand are considered. The simulation model is generated by an algorithm using results from the linear optimization approach.

A network economic model for supply chain versus supply chain competition

Abstract: We study a supply chain economy (SCE) that comprises heterogeneous SC involving multiple products and competing for multiple markets. The proposed network model is built upon operation links and interface links, representing, respectively, substantial SC operations and coordination functions between the operations. The paper presents a variational inequality formulation of the problem, the solution of which determines the winning SC and their market shares in the equilibrium of SCE. We furnish qualitative properties such as existence and uniqueness of the equilibrium. Numerical examples are presented for illustrative purpose.

Modeling the problem of locating collection areas for urban waste management. An application to the metropolitan area of Barcelona

Abstract: Reverse logistics problems arising in municipal waste management are both wide-ranging and varied. The usual collection system in UE countries is composed of two phases. First, citizens leave their refuse at special collection areas where different types of waste (glass, paper, plastic, organic material) are stored in special refuse bins. Subsequently, each type of waste is collected separately and moved to its final destination (a recycling plant or refuse dump). The present study focuses on the problem of locating these collection areas. We establish the relationship between the problem, the set covering problem and the MAX-SAT problem and then go on to develop a genetic algorithm and a GRASP heuristic to, respectively, solve each formulation. Finally, the quality of the algorithms is tested in a computational experience with real instances from the metropolitan area of Barcelona, as well as a reduced set of set covering instances from the literature.

On variance amplification in a three-echelon supply chain with minimum mean square error forecasting

Abstract: We analyse a three echelon supply chain model. First-order autoregressive end consumer demand is assumed. We obtain exact analytical expressions for bullwhip and net inventory variance at each echelon in the supply chain. All of the three supply chain participants employ the order-up-to policy with the minimum mean square error forecasting scheme. After demonstrating that the character of the stochastic ordering process observed at each level of the supply chain is mathematically tractable, we show that the upper stream participants have complete information of the market demand process. Then we quantify the bullwhip produced by the system, together with the amplification ratios of the variance of the net inventory levels. Our analysis reveals that the level of the supply chain has no impact upon the bullwhip effect, rather bullwhip is determined by the accumulated lead-time from the customer and the local replenishment lead-time. We also find that the conditional variance of the forecast error over the lead-time is identical to the variance of the net inventory levels and that the net inventory variance is dominated by the local replenishment lead-time.

An ant colony algorithm for solving budget constrained and unconstrained dynamic facility layout problems

Abstract: The main characteristic of today's manufacturing environments is volatility Under a volatile environment, demand is not stable It changes from one production period to another To operate efficiently under such environments, the facilities must be adaptive to changing production requirements From a layout point of view, this situation requires the solution of the dynamic layout problem (DLP) DLP is a computationally complex combinatorial optimization problem for which optimal solutions can only be found for small size problems It is known that classical optimization procedures are not adequate for this problem Therefore, several heuristics including taboo search, simulated annealing and genetic algorithm are applied to this problem to find a good solution This work makes use of the ant colony optimization (ACO) algorithm to solve the DLP by considering the budget constraints The paper makes the first attempt to show how the ACO can be applied to DLP with the budget constraints In the paper, example applications are presented and computational experiments are performed to present suitability of the ACO to solve the DLP problems Promising results are obtained from the solution of several test problems

Evaluating cost efficiency in central administrative services in UK universities

Abstract: This paper describes an attempt to evaluate cost efficiency in UK university central administration. The funding councils of higher education institutions have progressively evolved elaborate systems for measuring university performance in teaching quality and research. Indeed, funding of universities is linked to their performance in research. The allocation of resources between academic and administrative activities, on the other hand, has so far not been subject to scrutiny. Yet, expenditure on administration is typically some 30% of that allocated to academic activities. This paper sets up a data envelopment analysis (DEA) framework to identify practices leading to cost-efficient central administrative services in UK universities. The problems in defining the unit of assessment and the relationship between the inputs and the outputs are clearly demonstrated. © 2005 Elsevier Ltd. All rights reserved.

A process-oriented perspective of IS success: Examining the impact of IS on operational cost

Abstract: Effective measurement of information system (IS) success continues to be a top concern for both practitioners and researchers. Labeled the “productivity paradox”, previous attempts to quantify the benefits of IS have often resulted in inconclusive or inconsistent results. The present study contributes to IS success research through the development and empirical testing of a process-oriented model of IS success. Using an operational perspective and combining primary and secondary measures, this study examines the influence of lower-level intangible IS and information technology (IT) benefits on higher-level financial measures. Additionally, we introduce IS plan quality as an antecedent to the model's input variables. Primary survey data from CIOs of primarily Fortune 2000 size firms are combined with secondary data, total operational cost, from Compustat to facilitate the examination of the IS benefits. This study also addresses shortcomings cited in other studies that might have contributed to the productivity paradox by including control variables in the model, defining a research perspective—the operational success perspective—and clearly articulating the level of analysis as the organizational level. The results supported a process-oriented view of the benefits from IS and showed how the effects of IS along a path can lead to better organizational performance, in this case, lower overall costs. These results are discussed and future research implications are presented.

Disassembly to order system under uncertainty

Abstract: This paper presents a multi-criteria optimization model of a disassembly-to-order (DTO) system under uncertainty. The goal of the proposed model is to determine the best combination of the number of each product type to be taken back from the last user and/or collectors. The EOL products are then disassembled for the retrieval of reusable components and materials and resold in order to meet a certain level of demand under a variety of physical, financial and environmental constraints. The surplus components are recycled, stored for usage in subsequent periods or properly disposed. The problem is modeled as a multi-criteria decision-making problem under uncertainty, where the aspiration levels for various goals are more likely to be in the “approximately more (less) than” and/or “more (less) is better” form. We employ fuzzy goal programming technique to solve the problem. When solved, the model provides the number of EOL products to be taken back as well as the number of items reused, recycled, stored and disposed. The values of a host of other performance measures are also obtained, including total profit, materials and items sales revenues, take back cost, transportation costs as well as costs of preparation of EOL products, destructive disassembly, non-destructive disassembly, recycling, storage and disposal. A case example is presented to illustrate the model's implementation.

An interactive decision support system for an aggregate production planning model based on multiple criteria mixed integer linear programming

Abstract: In this paper, we present an aggregate production planning (APP) model applied to a Portuguese firm that produces construction materials. A multiple criteria mixed integer linear programming (MCMILP) model is developed with the following performance criteria: (1) maximize profit, (2) minimize late orders, and (3) minimize work force level changes. It includes certain operational features such as partial inflexibility of the work force, legal restrictions on workload, work force size (workers to be hired and downsized), workers in training, and production and inventory capacity. The purpose is to determine the number of workers for each worker type, the number of overtime hours, the inventory level for each product category, and the level of subcontracting in order to meet the forecasted demand for a planning period of 12 months. Additionally, a decision support system (DSS) based on the MCMILP model is proposed. It will help practitioners find the “best” solution for an APP problem without having to familiarize themselves with the mathematical complexities associated with the model. An example to illustrate the use of the DSS is also included.

Critical acceptance values and sample sizes of a variables sampling plan for very low fraction of defectives

Abstract: Acceptance sampling plans are practical tools for quality control applications, which involve quality contracting on product orders between the vendor and the buyer. Those sampling plans provide the vendor and the buyer rules for lot sentencing while meeting their preset requirements on product quality. In this paper, we introduce a variables sampling plan for unilateral processes based on the one-sided process capability indices C PU (or C PL ) , to deal with lot sentencing problem with very low fraction of defectives. The proposed new sampling plan is developed based on the exact sampling distribution rather than approximation. Practitioners can use the proposed sampling plan to determine accurate number of product items to be inspected and the corresponding critical acceptance value, to make reliable decisions. We also tabulate the required sample size n and the corresponding critical acceptance value C 0 for various α -risks, β -risks, and the levels of lot or process fraction of defectives that correspond to acceptable and rejecting quality levels.

Relationships among the academic business disciplines: a multi-method citation analysis

Abstract: A great number of papers have been published that compare the quality or impact of academic journals. This article seeks to broaden the debate on journal evaluation by showing how top journals in various academic business disciplines, as defined by the Financial Times list of top research outlets, relate to one other. Using large-scale sociometric analyses on about 140,000 citations we found that the integration of the citation network has increased over time. Moreover, the information flow from Finance and Economics to Management has become stronger and, within Management, a polarization between information generators and users has taken place. We also found that most business academics published in distinct and mostly non-overlapping disciplines. The only exceptions were Finance and Economics as well as Strategic Management and OB/HR. Surprisingly, we also found that the general business journals, which could be assumed to be cited by most other journals across the management disciplines, are not central to the entire field. For instance, they are not complementary at all to Finance and Economics. Instead, Operations Research (OR) and Management Information Systems journals occupy the central space on the perceptual map. This indicates that these disciplines (and OR in particular) are complementary with Management and with Finance and Economics.

Flow shop scheduling with deteriorating jobs under dominating machines

Abstract: This paper addresses no-wait or no-idle flow shop scheduling problems with deteriorating jobs, i.e., jobs whose processing times are an increasing function of their starting time. A simple linear deterioration function is assumed and some dominating relationships between machines can be satisfied. It is shown that for the problems to minimize makespan or weighted sum of completion time, polynomial algorithms still exist, although these problems are more complicated than the classical ones. When the objective is to minimize maximum lateness or maximum tardiness, the solutions of a classical version may not hold.

Dynamic performance of a hybrid inventory system with a Kanban policy in remanufacturing process

Abstract: In this paper we study a hybrid system with both manufacturing and remanufacturing. The inventory control strategy we use in the manufacturing loop is an automatic pipeline, inventory and order based production control system (APIOBPCS). In the remanufacturing loop we employ a Kanban policy to represent a typical pull system. The methodology adopted uses control theory and simulation. The aim of the research is to analyse the dynamic (as distinct from the static) performance of the specified hybrid system. Dynamics have implications on total costs in terms of inventory holding, capacity utilisation and customer service failures. We analyse the parameter settings to find preferred “nominal”, “fast” and “slow” values in terms of system dynamics performance criteria such as rise time, settling time and overshoot. Based on these parameter settings, we investigate the robustness of the system to changes in return yield and the manufacturing/remanufacturing lead time. Our results clearly show that the system is robust with respect to the system dynamics performance and the remanufacturing process can help to improve system dynamics performance. Thus, the perceived benefits of remanufacturing of products, both environmentally and economically, as quoted in the literature are found not to be detrimental to system dynamics performance when a Kanban policy is used to control the remanufacturing process.

Aligning operations, marketing, and competitive strategies to enhance performance: An empirical test in the retail banking industry

Abstract: The close linkage between competitive strategy and functional strategic activities is asserted to be a precondition to the achievement of optimal business performance. This study explores how the relationship between (and among) operations, marketing, and competitive strategies affects organizational performance in the banking industry. Our findings show that: (a) competitive strategy moderates the relationship between operations and marketing strategic activities, and organizational performance, (b) certain integrated strategic decisions of operations and marketing functions have a significant impact on organizational performance, and (c) the performance of retail banks within a strategic group differs depending on the quality of the strategic fit.

Total tardiness minimization on unrelated parallel machine scheduling with auxiliary equipment constraints

Abstract: This research deals with scheduling jobs on unrelated parallel machines with auxiliary equipment constraints Each job has a due date and requires a single operation A setup for dies is incurred if there is a switch from processing one type of job to another type For a die type, the number of dies is limited Due to the attributes of the machines and the fitness of dies to each, the processing time for a job depends on the machine on which the job is processed, each job being restricted to processing on certain machines In this paper, an effective heuristic based on threshold-accepting methods, tabu lists, and improvement procedures is proposed to minimize total tardiness An extensive experiment is conducted to evaluate the computational characteristics of the proposed heuristic Computational experiences demonstrate that the proposed heuristic is capable of obtaining optimal solutions for small-sized problems, and significantly outperforms an ATCS procedure and a simulated annealing method for problems in larger sizes

Precision parameter in the variable precision rough sets model: an application

Abstract: Despite their diverse applications in many domains, the variable precision rough sets (VPRS) model lacks a feasible method to determine a precision parameter ( β ) value to control the choice of β -reducts. In this study we propose an effective method to find the β -reducts. First, we calculate a precision parameter value to find the subsets of information system that are based on the least upper bound of the data misclassification error. Next, we measure the quality of classification and remove redundant attributes from each subset. We use a simple example to explain this method and even a real-world example is analyzed. Comparing the implementation results from the proposed method with the neural network approach, our proposed method demonstrates a better performance.

The effect of top management support of SISP on strategic is management : insights from the US electric power industry

Abstract: Strategic IS planning (SISP) is a fundamental tool of strategic IS management. Top management support of SISP, however, is often weak or absent. The association between this support and strategic IS management is important to an understanding of top management's role in the use of what has been acknowledged as a strategic tool. Strategic use of IS in US electric power companies is noteworthy because the industry is transitioning into a deregulated environment with increasing hostility and can provide special insights not available elsewhere. A postal survey of CIOs and other members of top management from 161 US companies, including 21 electric utility companies, revealed that top management support of SISP is strongly and significantly associated with strategic IS management. Top management support for SISP was present for both electrics and non-electric companies but results were mixed. CEOs exhibited only moderate participation in SISP although such participation was positively and strongly associated with strategic IS management. Overall, results suggest that top management support of SISP may increase when an industry transitions to a more hostile environment. Prescriptions are offered for improving top management support.

Sharing shipment quantity information in the supply chain

Abstract: This paper evaluates the benefit of a strategy of sharing shipment information, where one stage in a supply chain shares shipment quantity information with its immediate downstream customers—a practice also known as advanced shipping notice. Under a periodic review inventory policy, one supply-chain member places an order on its supplier every period. However, due to supplier’s imperfect service, the supplier cannot always exactly satisfy what the customer orders on time. In particular, shipment quantities arriving at the customer, after a given lead-time, may be less (possibly more) than what the customer expects—we define this phenomenon as shipment quantity uncertainty. Where shipment quantity information is not shared with customers, the only way to respond is through safety stock. However, if the supplier shares such information, i.e. customers are informed every period of the shipment quantity dispatched, the customer may have enough time to adapt and resolve this uncertainty by adjusting its future order decisions. Our results indicate that in most circumstances this strategy, enabled by information technologies, helps supply-chain members resolve shipment quantity uncertainty well. This study provides an approach to quantify the value of shared shipment information and to help supply-chain members evaluate the cost-benefit trade-off during information system construction. Numerical examples are provided to indicate the impact of demand/shipment parameters on strategy implementation. While previous studies mainly focus on the information receiver’s perspective, we evaluate a more general three-tier linear supply chain model via simulation, studying how this strategy affects the whole supply chain: the information sender, the information receiver and the subsequent downstream tier. 2005 Elsevier Ltd. All rights reserved.

Efficient frontiers for electricity procurement by an LDC with multiple purchase options

Abstract: In meeting its retail sales obligations, management of a local distribution company (LDC) must determine the extent to which it should rely on spot markets, forward contracts, and the increasingly popular long-term tolling agreements under which it pays a fee to reserve generator capacity. We address these issues by solving a mathematical programming model to derive the efficient frontier that summarizes the optimal tradeoffs available to the LDC between procurement risk and expected cost. To illustrate the approach, we estimate the expected procurement costs and associated variances that proxy for risk through a spot-price regression for the spot-purchase alternative and a variable-cost regression for the tolling-agreement alternative. The estimated regressions yield the estimates required to determine the efficient frontier. We develop several such frontiers under alternative assumptions as to the forward-contract price and the tolling agreement's capacity payment, and discuss the implications of our results for LDC management.

Identifying traffic safety best practice: an application of DEA and Malmquist indices

Abstract: DEA is used in this paper to investigate target achievements of the operational units of the Norwegian Public Roads Administration (NPRA) charged with traffic safety services. The DEA framework applied corresponds to a BCC model with a unique constant input, or equivalently, with no inputs. This framework is further extended to a DEA-based Malmquist index to measure productivity growth in target achievements. Finally, we use a bootstrapping method to ascertain confidence intervals for efficiency scores derived and to test hypotheses on the extent of productivity growth or regress. The mean efficiency scores by which targets are achieved across the sample years are in the range 0.81-0.93 and significant at the 5% level. Total productivity in target achievements shows progress with significance, on average at 7%. Much of the progress is attributed to technological progress. The results illustrate the usefulness of using a decomposable index for productivity measurement, and the use of bootstrapping for sensitivity tests.

An exploratory study of manufacturing strategy practices of machinery manufacturing companies in India

Abstract: This paper presents findings of a survey on manufacturing strategy practices adopted by the Indian machinery manufacturing companies (IMMC). Based on the survey, three companies have been selected for detailed case studies. Their experiences in the manufacturing strategy process are analyzed. Although the companies represented diversity in terms of product type, sales volume, and geographic location, they share several commonalties including use of advanced manufacturing technologies and use of several improvement techniques. The process of strategy formulation varied among the companies in terms of participants, complexity and degree of formalization. Competitive priorities, order winners and critical success factors are also identified for these companies. Based on strategic manufacturing issues, manufacturing competence index and business performance index for the companies has been worked out.