A decision support system for modelling and implementing the supply network configuration and operations scheduling problem in the machine tool industry

This paper presents a decision support system to simultaneously solve the supply network configuration problem and the operations scheduling problem for the machine tool industry. A novel database structure, which is able to consider alternative operations and alternative bills of material, has been used. An algorithm for complete enumeration to determine all the feasible solutions using stroke graphs is introduced. A multiagent-based simulator evaluates the different key performance indicators that the supply network deals with for each alternative solution (e.g. workload, profits, delivery times, etc.) to determine that ‘satisficed’ by the collaborative decision-making among its members. A case study based on a Spanish company that assembles highly customised machines and tools in several European plants is considered. From the experiments results based on data linked to this industry, it will be demonstrated that the tool is potentially useful for stakeholders and for the central decision-maker to make decisions collaboratively in a multisite context case.     

Freezing the master production schedule in multilevel material requirements planning systems under deterministic demand

This paper extends the studies by Sridharan, Berry, and Udayabhanu from single-level MPS systems to multilevel material requirements planning (MRP) systems, and examines the impact of product structure, lot-sizing rules and cost parameters upon the selection of MPS freezing parameters under deterministic demand. A model is built to simulate the master production scheduling and material requirements planning operations in a make-to-order environment. The results show that all the MPS freezing parameters studied have a significant impact upon total inventory costs and schedule instability in multilevel MRP systems. First, the order-based freezing method is preferable to the period-based method. Secondly, the study finds that increasing the freezing proportion reduces both total inventory costs and schedule instability. This finding contradicts the finding by Sridharan et al. in single-level systems. Thirdly, the study finds that a higher replanning periodicity results in both lower total inventory cost and lower schedule instability. The study also indicates that the product structure and lot-sizing rules do not significantly influence the selection of MPS freezing parameters in a practical sense under most situations. However, the cost parameter seems to significantly influence the selection of replanning periodicity.     

On the influence of a biased decision support model on subjects’ behavior

Summary  The role of decision tools in managerial decisions can be crucial. Yet, there is very little research seeking to understand and measure the influence of planning models on decision-makers’ actual behavior or performance. We focus on investigating, in an experimental context, the influence of a decision model (time allocation model) on student subjects’ changes of mind and behavior. Of special interest is the effect of the articulated importance of criteria on subjects’ choices. Furthermore, we have also studied how the above mentioned model influences subjects’ actual (measurable) performance. The results are partly conflicting, though interesting: (1) the (biased) decision model did have a significant influence on the subjects’ choices, (2) when the model provided additional freedom to improve criterion values, the subjects’ choices were rather inconsistent with the articulated importance of criteria, (3) the interpretation is not clear, how plans influence actual behavior, and (4) the subjects did not fully recognize the bias of the model (when present). However, our findings very clearly demonstrate that model developers have a great responsibility. Biased models may guide managers to make dramatically erroneous decisions in bona fide. We hope that our findings generate additional research into this important, but under-researched topic.      

A decision support methodology for strategic planning in maritime transportation

This paper presents a decision support methodology for strategic planning in tramp and industrial shipping. The proposed methodology combines simulation and optimization, where a Monte Carlo simulation framework is built around an optimization-based decision support system for short-term routing and scheduling. The simulation proceeds by considering a series of short-term routing and scheduling problems using a rolling horizon principle where information is revealed as time goes by. The approach is flexible in the sense that it can easily be configured to provide decision support for a wide range of strategic planning problems, such as fleet size and mix problems, analysis of long-term contracts and contract terms. The methodology is tested on a real case for a major Norwegian shipping company. The methodology provided valuable decision support on important strategic planning problems for the shipping company.     

Multicriteria decision support for global e-government evaluation

E-government refers to the use of information and communication technologies (ICT) by governments to provide digital services to citizens and businesses over the Internet, at local, national or international level. Benchmarking and assessing e-government is therefore necessary to monitor performance and progress by individual countries and identify areas for improvement. Although such measurements have already been initiated by various organizations, they scarcely highlight the multidimensional nature of the assessment. This paper outlines a multicriteria methodology to evaluate e-government using a system of eight evaluation criteria that are built on four points of view: (1) infrastructures, (2) investments, (3) e-processes, and (4) users’ attitude. The overall evaluation is obtained through an additive value model which is assessed with the involvement of a single decision maker–evaluator and the use of a multicriteria ordinal regression approach. Specifically, the UTA II method is used, whose interactive application process is divided in two phases. Its implementation is supported by MIIDAS (multicriteria interactive intelligent decision aiding system). This research work aims at supporting potential stakeholders to perform a global e-government evaluation, based on their own viewpoints and preferences. Finally, 21 European countries are evaluated and ranked considering the latest criteria data.     

The state of decision support systems: A review

Many organisations are now realising that information technology can make a significant contribution to their operations. Recent developments in decision support software are such that the time may have come when information technology will contribute significantly to managerial decision-making. This paper considers these developments alongside the organisational issues involved in decision-making, and the current position of IT in many mature organisations. The conclusion is that the new range of decision support software, whilst opening up further areas for computerised decision support, is unlikely to compete successfully for corporate IT funds. Use of the new tools will be restricted to small, isolated applications.     

A decision support system for a third-party coordinator managing supply chain with demand uncertainty

Global supply chains reduce cost but increase lead times, complexities and uncertainties. Retailers in consumer products industry are getting shorter lead time to respond to market demand. To meet this challenge, many rely on third party supply chain managers (SCMs) for economically supplying required quantities of finished products quickly. However, due to shorter ‘time to market’, the SCM has to procure raw materials and start production process based on expected demand. Since SCM absorbs financial penalties associated with under- and over-estimation of demand from retailer, finding an optimal production lot size and product customisation strategy are essential to an SCM's operation. We develop a profit maximisation model and provide a close-form solution that allows an SCM to calculate optimal production lot size. The model is used to examine profitability of postponing product customisation. Finally, the effect of demand variation on SCM's profitability is explored.     

Decision support tool for lean product and process development

Lean and concurrent engineering (CE) are widely acknowledged business process improvement strategies. These strategies can improve processes, reduce costs, and cut waste enabling organisations to remain competitive. Lean manufacturing offers an enterprise-wide methodology that improves reliability and flexibility while reducing lead-times and inventory carrying costs. Companies in manufacturing and service sectors are focusing on integrating lean manufacturing methodology with other applications, so that, all their systems and processes are aligned. This article proposes a CE framework based on application of information technology and object-oriented methodology for lean manufacturing. This approach expected to give manufacturing companies an extra edge in today's competitive market. A case study is presented in this article to demonstrate the effectiveness of CE framework in a machine tool manufacturing company. CE practice was adopted for new products, to align the systems and processes of the company. Product development lead-time was found to decrease by more than 50% compared to similar development projects carried out by the company. The need for rework was found to be negligible and the development cost was reduced considerably.     

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

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.     

A hierarchical production plan for a make-to-order steel fabrication plant

A three-tiered hierarchical production plan (HPP) for a strictly make-to-order steel fabrication plant with the objective of developing a production plan and master schedule for a set of product archetypes is implemented. Data are collected from an actual steel fabrication plant located in the Midwestern section of the US. An aggregate linear programming model, a non-linear disaggregate model and a master production schedule comprise the respective tiers. Appropriate models provide the forecasts needed in the first two tiers. A production plan and master schedule based on data collected at the plant, benefits expected for its implementation and practical limitations are reported.     

基于神经网络的期货套期保值决策支持系统

针对期货套期保值业务的特点 ,分析了期货套期保值决策支持系统的整体逻辑 ,尝试用人工神经网络专家系统预测期货行情走势 ,介绍了如何将期货市场与 BP网络有机结合起来构造适合期价预测的模型 ,并且在实证分析中给出了寻找最优预测效果的方法以及预测结论应用分析 .同时 ,提出了以此分析为基础的 DSS系统结构和功能 ,对辅助套期保值者决策有一定的指导意义     

Production planning and control as a tool for eco-efficency improvement and environmental impact reduction

The environmental impacts of industrial activity are an increasing concern amongst firms and their stakeholders. As a result, companies around the world have been exploring new tools to diminish the adverse impact of their activities on the environment. Eco-efficiency has played an essential role in this scenario, as companies are continuously seeking to produce more while utilizsing fewer resources and minimising adverse effects on the environment. The literature includes several initiatives to improve eco-efficiency and to reduce the environmental impact of manufacturing operations, but the use of production planning and control (PPC) activities to accomplish these goals has rarely been considered. Therefore, to contribute to the assessment of this issue, this paper proposes to integrate environmental concepts and actions as part of the PPC execution; therefore, they could also be applied to minimise environmental impacts, resulting in an increase in the eco-efficiency level of a company. The practical utilisation of the suggested procedure was confirmed using a case study where the procedure was successfully applied to a make-to-order firm, where a simplified version of a workload control (WLC) form of PPC was in use. As a result, incorporating environmental considerations into the WLC practices enabled the eco-efficiency level of the designated production area to increase by 42%, while the environmental impact of production was reduced by 13%.     

A robust optimization model for stochastic aggregate production planning

The aggregate production planning (APP) problem considers the medium-term production loading plans subject to certain restrictions such as production capacity and workforce level. It is not uncommon for management to often encounter uncertainty and noisy data, in which the variables or parameters are stochastic. In this paper, a robust optimization model is developed to solve the aggregate production planning problems in an environment of uncertainty in which the production cost, labour cost, inventory cost, and hiring and layoff cost are minimized. By adjusting penalty parameters, decision-makers can determine an optimal medium-term production strategy including production loading plan and workforce level while considering different economic growth scenarios. Numerical results demonstrate the robustness and effectiveness of the proposed model. The proposed model is realistic for dealing with uncertain economic conditions. The analysis of the tradeoff between solution robustness and model robustness is also presented.     

A structured procedure for materials planning during production transfer

This paper explores materials planning procedures to ensure the materials’ availability during production transfers. The paper defines a production transfer as the preparation, physical transfer and start-up of relocated production. A structured procedure of materials planning during production transfer is developed based on theory, and then validated and refined based on the analysis of four case studies. The paper shows that there is a need for a structured procedure of materials planning during production transfers. It also explains the importance of activities that create prerequisites for the materials’ availability during production transfer, such as updating and adapting documentation, planning and control systems, and describes the activities that ensure the materials’ availability, such as preventive and corrective actions. A valid estimation of the time needed to reach a steady state and a combination of several preventive actions improves the ability to ensure that materials are available. The cases showed differences across company size, because large companies took more and farther-reaching preventive actions.     

A quantitative field study of the decision behaviour of four shopfloor schedulers

In this article the decision behaviour of four production schedulers in a truck manufacturing company is investigated by means of a quantitative model. The model consists of there parts: performance variables, action variables and disturbance variables. The outcomes show that there is a large difference between schedulers that apparently have the same type of decision problem. Another interesting finding is that some scheduling actions work positively in the short term, but negatively over a longer term. Other results, along with methodological issues of quantitative research, are discussed.     

A review of hierarchical production planning and its applicability for modern manufacturing

The hierarchical production planning (HPP) paradigm has become an accepted planning and control strategy for many medium-to-large manufacturing situations. While the paradigm appears intuitively obvious and appropriate for many factories, there are a number of modern manufacturing situations where the application of the HPP approach may not be appropriate. By understanding the fundamental principles and concepts inherent in the HPP approach, it is possible to identify situations suitable for HPP with little or no adaptation, and situations where HPP must be extensively modified before use. A poor understanding of HPP     

A multicriteria decision analysis model for faculty evaluation

In the context of increasing demands for social and financial accountability of universities, the required implementation of transparent faculty evaluation systems constitutes a challenge and an opportunity for universities strategically aligning the activity of academic staff with the university goals. However, despite growing interest in the performance appraisal of faculty, only a few reported studies propose models that cover the full range of academic activities and the models in use are typically based on ad hoc scoring systems that lack theoretical soundness. This article approaches faculty evaluation from an innovative comprehensive perspective. Based on the concepts and methods of multiple criteria value measurement, it proposes a new faculty evaluation model that addresses the whole range of academic activities and can be applied within and across distinct scientific areas, while respecting their specificities. Constructed through a socio-technical process, the model was designed for and adopted by the Instituto Superior Técnico, the engineering school of the Technical University of Lisbon. The model has a two-level hierarchical additive structure, with top-level evaluation areas specified by second-level evaluation criteria. A bottom non-additive third level accounts for the quantitative and qualitative dimensions of academic activity related to each evaluation criterion. The model allows (a) the comparison of the performance of academic staff with performance targets reflecting the strategic policy concerns of university management; (b) the definition of the multicriteria value profile of each faculty member at the top level of the evaluation areas; (c) the computation of an overall value score for each faculty member, through an optimisation procedure that makes use of a flexible system of weights and (d) the assignment of faculty members to rating categories.     

A technique for uncertainty reduction based on order commonality

The use of commonality is widely diffused as a criterion to reduce uncertainty in demand forecasts for the master production schedule (MPS). Nevertheless, studies have mostly focused on exploiting component commonality in make to stock and assemble to order manufacturing. This paper refers to planning environments with two specific characteristics. First, the degree of certainty of the demand is extremely low, due to product complexity, with poor modularization and standardization, and to the presence of few customers of large dimensions. Second, the delivery lead time is less than the total lead time. In this situation, demand for MPS planning units is extremely uncertain and sporadic. It is therefore necessary to formulate in advance forecasts of customer orders with a redundant configuration. In this paper a technique for the reduction of demand uncertainty is introduced, based on the exploitation of order commonalities. In particular, relations between order commonality and uncertainty reduction in a planning environment with such complex features are illustrated. Then, guidelines for the implementation of the technique in order to reduce over-planning in the master production schedule are provided. Finally, the performances of the technique are empirically analysed by means of both a simulation model and experimental application in a telecommunication systems manufacturer     

A variability taxonomy to support automation decision-making for manufacturing processes

Abstract

Although many manual operations have been replaced by automation in the manufacturing domain in various industries, skilled operators still carry out critical manual tasks such as final assembly. The business case for automation in these areas is difficult to justify due to increased complexity and costs arising out of process variabilities associated with those tasks. The lack of understanding of process variability in automation design means that industrial automation often does not realize the full benefits at the first attempt, resulting in the need to spend additional resource and time, to fully realize the potential. This article describes a taxonomy of variability when considering the automation of manufacturing processes. Three industrial case studies were analyzed to develop the proposed taxonomy. The results obtained from the taxonomy are discussed with a further case study to demonstrate its value in supporting automation decision-making.     

A review of capacity planning techniques within standard software packages

This paper gives a review of capacity planning techniques from which today's standard software packages for production control make their choice. The following techniques are discussed in the paper: four variants of the rough cut capacity check, capacity requirements planning with infinite and finite loading, input/output planning without and with individual work orders, and a number of sequencing techniques. An important issue throughout the paper is the concept of robustness and nervousness of planning techniques, Aspects of interaction between techniques and human planners arc given. The human planner is still an important factor in capacity planning.