A step-by-step guide to the identification of an appropriate computer-aided production management system

The increasing dissatisfaction of users with their Computer-aided production management (CAPM) systems has been widely reported. This dissatisfaction led the UK's Science and Engineering Research Council to initiate a major study to improve CAPM systems use. The research results presented here form part of the overall initiative and focus on the development of a set of guiding principles for companies seeking to implement appropriate CAPM systems. The research team have identified three key elements that must be considered when implementing a CAPM system. First, that CAPM implementation can be eased if the overall manufacturing-system is first simplified. Second, we recognize that even then most companies will still require a computerized solution thus any methodology must include a software specification. Third, the overall performance of the system may be enhanced by changes to the infrastructure that supports the software. In attempting to meet these requirements the research team developed a four-stage methodology. The first two stages of the methodology deal primarily with the strategic context for CAPM, i.e. the simplification. The last two stages develop a software specification and present guidelines for the development of appropriate infrastructure configurations.     

带有快速反应策略供应链系统的补偿策略研究

过长的订购提前期往往使得零售商订货决策感到困难. 快速反应策略能使零售商在获 得更多更准确的市场需求信息后,调整订购量而提高收益. 但是快速反应策略并不一定使供应 商的利润也提高. 有文章指出只有低的服务水平才能使两者利润同时提高,因而这种方法在工 业应用中是不一定可行的. 补偿策略是一种广泛应用的方法,能够提高产品的客户服务水平, 因而研究了补偿策略在快速反应供应链系统中的作用. 在某些条件下,在快速反应供应链系统 中,补偿策略能使零售商与供应商一方的收益不变或者提高,另一方的收益有所提高,即Pare2 to 提高. 还研究了引进补偿策略后,供应链系统的最优解及期望卖出量、期望缺货量和期望残 余量的变化情况.     

A modified hierarchical production planning system integrated with MRP: A case study

In this paper, a hierarchical planning system is proposed which integrates aggregate capacity planning with MRP. This system is to be implemented in a metal box manufacturing company which multi-user MRP system covering manufacturing activities as well as procurement sales order processing and accounting systems. The hierarchical planning system includes a medium-range aggregate planning model adapted to the firm's requirements and strategies. The model consists of a mathematical formulation which covers labour capacity has already installed a constraints and includes certain cost estimations in the objective function. The planning horizon of the medium range planning is taken as twelve months in order to cover sales seasonality. The aggregate production quantities resulting from the optimized medium-range planning model are disaggregated according to procedures already found in the literature. Furthermore, the theoretical infeasibilities pertaining to the disaggregation procedures are also resolved in an heuristic manner. Using the latter modified disaggregation procedure, a feasible disaggregated plan is generated for the whole planning horizon. The proposed plan is compared with the current production policy of the firm and it is observed that the proposed plan leads to backorder reduction.     

A framework for production control in health care organizations

The paper presents a hierarchical framework for production control of hospitals which deals with the balance between service and efficiency, at all levels of planning and control. The framework is based on an analysis of the design requirements for hospital production control systems. These design requirements are translated into the control functions at different levels of planning required for hospital production control. The framework consists of five levels of planning and control: patient planning and control, patient group planning and control, resources planning and control, patient volumes planning and control and strategic planning, though this last level does not make part of production control as such. Each of the levels of the framework is further elaborated in terms of the decisions made regarding patient flows and resources, and the co-ordination of the different planning levels. Implications of the framework are discussed by describing some points where current practice deviates from assumptions made in our approach. Recommendations for future research and development of the planning framework are formulated.     

Relation between market orientation and market environment et al., in Korean firms entering to North American markets

This study was conducted to test the antecedent factors of market orientation and the relationship between market orientation and business performance of overseas subsidiaries. The author also investigates whether competitive strategy might affect the strength or weakness of the market orientation—performance relationship. The results of research show that the magnitude of the firm and market turbulence have significance as antecedent factors of market orientation, and competitive strategy can also moderate the relationship between market orientation and performance. Lastly, the results show that the relationship between market orientation and performance has a positive significance.     

Multi-site aggregate production planning with multiple objectives: A goal programming approach

This paper addresses the problem of aggregate production planning (APP) for a multinational lingerie company in Hong Kong. The multi-site production planning problem considers the production loading plans among manufacturing factories subject to certain restrictions, such as production import/export quotas imposed by regulatory requirements of different nations, the use of manufacturing factories/locations with regard to customers' preferences, as well as production capacity, workforce level, storage space and resource conditions of the factories. In this paper, a multi-objective model is developed to solve the production planning problems, in which the profit is maximized but production penalties resulting from going over/under quotas and the change in workforce level are minimized. To enhance the practical implications of the proposed model, different managerial production loading plans are evaluated according to changes in future policy and situation. Numerical results demonstrate the robustness and effectiveness of the developed model.     

Models to explore remanufacturing as a competitive strategy under duopoly

Remanufacturing is a product recovery option that upgrades the quality of returns to “as-good-as-new” conditions. Remanufactured products cost less, and are sold with the same or better warranty as for new products. In this paper, we consider a duopoly environment with two manufacturers in direct competition selling their respective new products on the primary market. Specifically, we address the question: In case one manufacturer decides to remanufacture and sell remanufactured products on the price-sensitive secondary market, will it get a competitive advantage over the other manufacturer? We develop theoretical models for a single period and two periods, and show that under the stated assumptions, remanufacturing is almost always more profitable than when there is no remanufacturing. Although remanufacturing may cannibalize new product sales, the combined profitability and market share of the (re)manufacturer on account of new and remanufactured product sales improve over new product sales only. For the competitor, we get mixed results. In some situations, its profitability improves; in some others, it worsens. We also conduct sensitivity analyses with respect to the substitution parameters, price-sensitivity of the secondary market, rate of return of used products (cores), relative market shares of the manufacturers, and relative sizes of the primary and secondary markets. We conclude the paper with managerial implications and directions for future research.     

A neural network clustering model for miscellaneous components production planning

The growing importance of providing service to customers, e.g. post-sale assistance, supplying of spare parts, upgrading and integration of new elements in installed systems, enhances the importance of planning and management of upgrading parts in most manufacturing industries. These parts are generally characterized by high technical heterogeneity and have a highly variable and difficult to forecast demand. In some areas (especially the most dynamic, e.g. high-tech products), these kinds of components are quite common, and represent a very strong relation between the manufacturing firm and the market. These parts are generally too many to be efectively supported on a planning database system with individual records and too heterogeneous ( and sometimes with a too high value) to be supported all together in a single record. In this paper, we want to study the application of adaptive techniques for the clustering of these components in classes based on the similarities in their market behaviour in order to build an optimal database for planning production and supplying of these components.     

Optimal price,warranty length and production rate for free replacement policy in the static demand market

In the present paper, a decision model is developed for producers in the static demand market to determine the optimal price, warranty length and production rate of a product to maximize profit based on the pre-determined life cycle. The free renewal warranty policy is considered under which failed products are renewed before the end of warranty length at no cost to consumers. The expected number of renewals based on warranty length is derived for Weibull life distributed products. The objective function includes both demand and cost functions, where production cost, warranty cost and inventory cost are involved. A solution approach using the maximum principle is described, and is applied to two specific cases of markets. The first case of market considers positive discount rate, and the second case of market considers zero discount rate. The economic sensitivity analysis is conducted to evaluate the effect of model parameters on the optimal solution. Some conclusions are drawn based on the sensitivity analysis.     

A real options model of market entry: Endogenous uncertainty and exogenous uncertainty

We develop a real options model of market entry that focuses on the dueling growth and deferral options by differentiating between endogenous uncertainty and exogenous uncertainty. While exogenous uncertainty influences the growth option market value or price, it is endogenous uncertainty that influences the value of the growth option through the ability to create a competitive advantage from preemptive market entry. First, the firm can decrease the exercise price of the growth option (i.e., the cost of the follow-on investment) through experiential learning that reduces endogenous uncertainty. Second, the firm can increase the relative discounted cash flows of the follow-on investment due to its ability to influence market demand that reduces endogenous uncertainty. On the other hand, the value of the deferral option increases with exogenous uncertainty as firms cannot influence exogenous uncertainty, and therefore, should invest elsewhere while waiting for the exogenous uncertainty to subside. As such, we provide a solution to the conundrum that the value of both the growth option and the deferral option increase with uncertainty. Finally, we demonstrate how the model addresses sequential market entry; irreversibility and market entry mode; competition; scarce strategic resources; host country development level; and industry life cycle stage.     

从“市场导向”到“引导市场”:营销观念的转变

本文论述了“引导市场”策略的含义及其与其他传统策略的异同,提出了已定型的企业实施该策略的障碍与措施.     

A hybrid inventory management system responding to regular demand and surge demand

This paper proposes a hybrid policy for a stochastic inventory system facing regular demand and surge demand. The combination of two different demand patterns can be observed in many areas, such as healthcare inventory and humanitarian supply chain management. The surge demand has a lower arrival rate but higher demand volume per arrival. The solution approach proposed in this paper incorporates the level crossing method and mixed integer programming technique to optimize the hybrid inventory policy with both regular orders and emergency orders. The level crossing method is applied to obtain the equilibrium distributions of inventory levels under a given policy. The model is further transformed into a mixed integer program to identify an optimal hybrid policy. A sensitivity analysis is conducted to investigate the impact of parameters on the optimal inventory policy and minimum cost. Numerical results clearly show the benefit of using the proposed hybrid inventory model. The model and solution approach could help healthcare providers or humanitarian logistics providers in managing their emergency supplies in responding to surge demands.     

A general approach to disassembly planning and control

Closing product and material cycles have emerged as a paradigm for industry in the 21st century, and are directed towards an economical and responsible use of our limited resources. Disassembly plays a key role in recycling. It enables the recovery of functioning components for re-use of pure materials for re-utilization and the separation of harmful substances. Major challenges are presented by the enormous variety of products to be disassembled, by uncertainty as to quantity and by their unknown properties. An appropriate planning and control of disassembly processes is essential for an economic disassembly. Based on an investigation of the suitability of common production planning and control (PPC) methods for disassembly, a specific disassembly planning and control concept (DPC) is outlined.     

A demand classification scheme for spare part inventory model subject to stochastic demand and lead time

In this study, we aim to develop a demand classification methodology for classifying and controlling inventory spare parts subject to stochastic demand and lead time. Using real data, the developed models were tested and their performances were evaluated and compared. The results show that the Laplace model provided superior performance in terms of service level, fill rate (FR) and inventory cost. Compared with the current system based on normal distribution, the proposed Laplace model yielded significant savings and good results in terms of the service level and the FR. The Laplace and Gamma optimisation models resulted in savings of 82 and 81%, respectively.     

A generic accounting model to support operations management decisions

Information systems are generally unable to generate information about the financial consequences of operations management decisions. This is because the procedures for determining the relevant accounting information for decision support are not formalised in ways that can be implemented in information systems. This paper describes a formalised procedure, which is based on the following theoretical propositions: (i) cost behaviour is described on the basis of a company's contracts for purchasing and selling resources, and (ii) hierarchical relationships between decisions are recognised, because some decisions have to be made earlier than others. Earlier decisions determine the feasible alternatives for later decisions (e.g. through constraints in available production capacity or components), and the plans that supported the earlier decisions serve as instructions for later decisions. The procedure can be implemented in information systems to provide accounting information in case later decisions deviate from these instruc tions (within the limits of the real-world constraints) because new information becomes available.     

A Computational Study of Replicated Clustering with an Application to Market Segmentation*

In most commercial applications of k-means clustering, researchers choose one set of kseed points to start the partitioning process; often, the initial set of seeds is chosen randomly. Using Monte Carlo simulation, we show that significant benefits are associated with replicated starting configurations that incorporate seed selection procedures based on a hierarchical clustering of sample points drawn from the original data matrix. A real-world application of the approach is then presented.     

Response strategy to environment context factors using a lean and agile approach: Implications for firm performance

Based on the environment-strategy performance perspective and dynamic capabilities framework, we develop a theoretical model and hypotheses specifying how supply chain collaboration as a response to environment context factors – competitive intensity, supply uncertainty, technological turbulence and market turbulence, using a lean and agile strategy may influence firm performance. We test the model using partial least square structural equation modelling on data collected from a field survey with responses from 152 manufacturing firms representing a variety of industries. Empirical findings generally support the relationship between collaboration and firm performance using a lean and agile strategy. Also, for firms in industries that face environments characterised by high supply uncertainty and competitive intensity with, technological turbulence, the study finds evidence of a direct relationship between these environmental factors and supply chain collaboration. The findings provide an initial strategic response framework for appropriately aligning a lean and agile supply chain strategy through collaboration with environment context factors to achieve firm performance improvements.     

A Strategic,Area-wide Contingency Planning Model for Oil Spill Cleanup Operations with Application Demonstrated to the Galveston Bay Area*

This paper develops a general integer programming model for strategic, area-wide contingency planning of oil spill cleanup operations. Model inputs include the set of risk points and the likely spill scenarios and response requirements for each, the sites of existing storage locations and the inventory of components at each, and potential sites for new storage locations. The model prescribes a minimum total cost plan to either build new storage locations, expand existing ones, or both, to purchase new components and pre-position them, and a contingency plan that determines which response systems should be composed to enable an effective time-phased response for each likely spill scenario. A family of heuristics based on linear programming (LP) is devised to resolve this strategic problem, providing an area-wide contingency plan. The heuristics are evaluated on a set of 10 test problems that involve 1869 general integer variables and 3264 constraints. Computational tests indicate that four heuristics are quite effective, prescribing solutions for each of 10 test cases within 1.41% of optimum and within a few minutes runtime. This study focused on modeling the Galveston Bay Area, and the test problems represent application in that area. A sensitivity analysis is demonstrated by assessing the impacts of component availability and the degradation of cleanup capability over time. Use of the model as a decision support aid by responsible parties, contractors, governmental organizations and others is described.     

A heuristic approach to long-haul freight transportation with multiple objective functions

This paper studies a long-haul freight transportation problem stimulated by a real-life application, whose underlying vehicle routing problem is a multi-objective one, where travel time and route cost are to be minimized together with the maximization of a transportation mean sharing index, related to the capability of the transportation system of generating economy scale solutions. In terms of constraints, besides vehicle capacity and time windows, transportation jobs have to obey additional constraints related to mandatory nodes (e.g., logistic platform nearest to the origin or the destination) and forbidden nodes (e.g., logistic platforms not compatible with the operations required). Based on the network definition, routes can be multimodal. To solve this problem, we propose a heuristic algorithm that can be applied in the tactical and the operational planning phase, and present the results of an extensive experimentation.