Application of an MRP matrix-based hierarchical planning model to a furniture company

This paper is concerned with the definition of a feasible master schedule for operations management, obtained through an integrated planning system, using a hierarchical methodology (by means of different disaggregation stages) with an appropriate time horizon for connection with the manufacturing requirements planning unit (MRP II). The hierarchical model obtained considers not only product aggregation into types, families and items but also resources aggregation, structure of products aggregation or bill-of-materials aggregation, as well as temporary aggregation. It allows the creation of a master schedule for an adequate time horizon, that can be used as an     

Dissaggregation of deviations in cost analysis

The decisions on investigation of cost deviations have been generally discussed in the cost control literature assuming deviations are monitored and reported at a certain level of aggregation. This paper focuses on the relationship between the level of aggregation of the reporting system and the effectiveness of the investigating decisions. It suggests that, by incorporating into the decision process the prior knowledge managers have about the deviation sources, the deviation report could be further disaggregated leading to improved investigation decisions. This is done by using the reported deviation to update the prior distribution of its possible sources in a Bayesian manner. The resulting system is less costly to monitor than a system which monitors all the possible sources of a deviation, although it is less exact. The paper illustrates how the selection of the optimal level of aggregation should be made simultaneously with the information system and the decision rules.     

A model for an integrated manufacturing system implementation in China: a case study

This paper describes a process which a company adopted to enhance her manufacturing system in a step-by-step manner. In order to increase the competitiveness of the company, the authors have identified a number of improvement strategies which were specific to the economic and political environment in China. The center of the strategies is a vision of an integrated manufacturing strategy. The detailed design and implementation of this vision is conducted through the proposed systematic manufacturing strategic analysis. The integration process encompasses various elements such as Total Quality Management (TQM), Manufacturing Resources Planning (MRPII) and Real-Time Monitoring System (RTMS), it emphasises not only the use of appropriate modern technology but also the management of technology change. In this paper, a concept model is used to describe the integration process, the detailed implementation is also elaborated using a proposed implementation process model. By adopting the integrated manufacturing system, and through continuing improvement, the productivity and hence the profitability of the company is increased. It is anticipated that the integrated approach to the design and implementation of manufacturing systems will be an important contribution towards the manufacturing strategy in a labour intensive environment such as China.     

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.     

CAPACITY AND PRODUCTION DECISIONS IN STOCHASTIC MANUFACTURING SYSTEMS: AN ASYMPTOTIC OPTIMAL HIERARCHICAL APPROACH

We present a new paradigm of hierarchical decision making in production planning and capacity expansion problems under uncertainty. We show that under reasonable assumptions, the strategic level management can base the capacity decision on aggregated information from the shopfloor, and the operational level management, given this decision, can derive a production plan for the system, without too large a loss in optimality when compared to simultaneous determination of optimal capacity and production decisions. The results are obtained via an asymptotic analysis of a manufacturing system with convex costs, constant demand, and with machines subject to random breakdown and repair. The decision variables are purchase time of a new machine at a given fixed cost and production plans before and after the purchase. The objective is to minimize the discounted costs of investment, production, inventories, and backlogs. If the rate of change in machine states such as up and down is assumed to be much larger than the rate of discounting costs, one obtains a simpler limiting problem in which the random capacity is replaced by its mean. We develop methods for constructing asymptotically optimal decisions for the original problem from the optimal decisions for the limiting problem. We obtain error estimates for these constructed decisions.     

Planning of a decentralized distribution network using bilevel optimization

This paper proposes a bilevel optimization problem to model the planning of a distribution network that allows us to take into account how decisions made at the distribution stage of the supply chain can affect and be affected by decisions made at the manufacturing stage. Usually, the distribution network design problem decides on the opening of depots and the distribution from the depots to customers only and pays no attention to the manufacturing process itself. By way of example, the paper discusses the implications of formulating a bilevel model to integrate distribution and manufacturing, maintaining the hierarchy existing in the decision process. The resulting model is a bilevel mixed integer optimization problem. Hence, only small instances can be optimally solved in an acceptable computing time. In order to be able to solve the optimization model for realistic large systems, a metaheuristic approach based on evolutionary algorithms is developed. The algorithm combines the use of an evolutionary algorithm to control the supply of depots with optimization techniques to determine the delivery from depots to customers and the supply from manufacturing plants to depots. A computational experiment is carried out to assess the efficiency and robustness of the algorithm.     

Simulation-based production schedule generation

Abstract

While simulation has been used in manufacturing for many years, predominantly for facility design, it is within the last few years, that simulation languages have been developed to a point where they can be used on a day-to-day basis to generate schedules and predict their performance. This paper describes our use of different modelling techniques to develop a production schedule generation system. An example describing a system for a small- to medium-sized order producing company using SIMAN/CINEMA is included. While addressing the shortcomings of existing scheduling systems it is shown how the approach taken is a feasible way of creating a dynamic goal-driven simulation-based production scheduler. The paper does not aim to describe an ‘off the shelf’ scheduling system product, but rather to give an overview to methods, techniques and experiences which enable us rapidly to tailor a simulation-based scheduling system to the specific needs of a company.     

Dynamic issues in the planning and control of integrated manufacturing hierarchies

Integrated manufacturing operations typically are organized along hierarchical lines. Characterized by product aggregation and time horizon, hierarchical decompositions aim at easing problems associated with the complexity and scale of the manufacturing function taken as a whole. Static models have been developed and employed which facilitate the analysis and functioning of these organizations. Existing models are valuable aids in assisting goal-planning functions, but provide little guidance for directing the pursuit of goals. This paper presents a new hierarchical model of integrated manufacturing operations based on concepts of management control. The model is congruent with commonly used static planning models, while at the same lime depicting real-time, goal-achievement efforts within a dynamic operating environment. Emphasizing the interactions between goal planning and goal achievement, the dynamic model provides a means of assessing the effects of decentralization and autonomy on the goal planning and achievement process. The model is used to identify two resource-consuming chain reactions linked to replanning and goal pursuit within the hierarchy. A simple example based on the dynamic extension of a typical static decomposition illustrates the key findings.     

A reactive approach to material procurement in an SME

The purpose of this paper is to introduce a more reactive approach to material procurement in a small manufacturing enterprise (SME). The approach involves a hybrid top-down and bottom-up approach to the issue of material procurement. The implementation of the approach in the test site is discussed and we show how the company can benefit from its implementation. The approach requires that there is a good interaction and transfer of information between an SME and both its customers and suppliers. The approach also requires a manufacturing firm to have control of the shopfloor and to have access to relevant and accurate information from the shopfloor. This hybrid approach to material procurement coupled with improved production activity control has helped a local manufacturing company to increase its reactivity. A decision support software tool is available which supports this approach and is described in the paper.     

Schedule nervousness in a manufacturing system: a case study

Schedule nervousness has received significant attention from the academics for almost three decades. However, the majority of published works on schedule nervousness have relied upon experimental results as a basis for making conclusions and there appears to be very little field-based evidence presented in the relevant literature. This paper presents a case study of schedule nervousness based on field observations in a shoe manufacturing company in Indonesia. A model to quantify nervousness is also presented. This study provides an insight that schedule nervousness is an important issue in practice and efforts to quantify nervousness, as well as to understand how it occurred, are necessary in order to reduce nervousness.     

Cost‐Benefit Analysis for Optimization of Risk Protection Under Budget Constraints

Cost‐benefit analysis (CBA) is commonly applied as a tool for deciding on risk protection. With CBA, one can identify risk mitigation strategies that lead to an optimal tradeoff between the costs of the mitigation measures and the achieved risk reduction. In practical applications of CBA, the strategies are typically evaluated through efficiency indicators such as the benefit‐cost ratio (BCR) and the marginal cost (MC) criterion. In many of these applications, the BCR is not consistently defined, which, as we demonstrate in this article, can lead to the identification of suboptimal solutions. This is of particular relevance when the overall budget for risk reduction measures is limited and an optimal allocation of resources among different subsystems is necessary. We show that this problem can be formulated as a hierarchical decision problem, where the general rules and decisions on the available budget are made at a central level (e.g., central government agency, top management), whereas the decisions on the specific measures are made at the subsystem level (e.g., local communities, company division). It is shown that the MC criterion provides optimal solutions in such hierarchical optimization. Since most practical applications only include a discrete set of possible risk protection measures, the MC criterion is extended to this situation. The findings are illustrated through a hypothetical numerical example. This study was prepared as part of our work on the optimal management of natural hazard risks, but its conclusions also apply to other fields of risk management.     

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.     

Coordination and Priority Decisions in Hybrid Manufacturing/Remanufacturing Systems

Companies are increasingly realizing the need to coordinate their manufacturing and remanufacturing operations. This can be a challenge due to the inherent variability in the condition and amount of returns, which has a direct impact on remanufacturing costs and leadtimes. In this paper, we develop a modeling framework to compare two alternative strategies that use either manufacturing or remanufacturing as the primary means of satisfying customer demand. Of course, in the event that the demand cannot be met by the prioritized process, the secondary process is used as a contingency. In our basic model, the priority decisions are made at the component level in replenishing the serviceable inventory, while the disposal and new component ordering decisions are made independently. The second model represents the coordination of remanufacturable and new component inventory control decisions. Using simulation‐based optimization on a large number of experiments, we observe that when prioritization is in the upstream echelon and there is no coordination in managing component stocks, there exists a critical return ratio, below which it is beneficial to give priority to manufacturing and above which it is beneficial to give priority to remanufacturing. We also see that coordinated control of the component inventories considerably reduces the importance of prioritization. These observations remain valid when congestion in the shop floor is also taken into account. We also study the benefits of state‐dependent dispatching policies in a realistic case.     

Decision model for product rollover in manufacturing operations

The purpose of this study is to investigate critical decisions when planning for product rollover at a manufacturing company, and how to organise these decisions. A literature review and a case study are used to develop a decision model. The findings indicate that product rollover can be organised in a five-phase decision model. The research quality is strengthened by a structured literature review, but it can be argued that more empirical research is needed for validation. For researchers, this paper contributes with the identification of critical decisions and a model for product rollover. For practitioners, the study highlights the need to acknowledge the importance of product rollover and its role as a competitive weapon. In earlier studies, product rollover has mainly been investigated from a market perspective, so that this study contributes by investigating the issue from a manufacturing perspective.     

The effects of managerial decision making behaviour and order book size on workload control system implementation in Make-To-Order companies

Insufficient attention has been paid to behavioural influences on the implementation of the ‘Workload Control’ (WLC) concept – a Production Planning and Control (PPC) approach for small and medium sized Make-To-Order companies – and there is an implicit assumption that managers are rationalistic in their decision-making. This paper analyses the effects of both managerial decision-making behaviour and the size of a company’s order book, affecting the number of decisions that have to be made, on two case study implementations of a WLC system. The Recognition-Primed Decision (RPD) model from the Naturalistic Decision-Making literature is used to unpack the first case where implementation failed. This highlighted a misalignment between how the company’s owner-manager initially made operational decisions and how a rationalistic WLC system functions. But the company is studied over six years, allowing us to show how the owner-manager was forced to transition from the RPD model to a more rationalistic approach to PPC as the size of the order book increased. A second case study is then briefly presented in which WLC system implementation was successful; the RPD model was not strongly evident and the size of the order book was greater to begin with. The paper helps to understand the decision-making behaviour of managers in small companies and how it may conflict or be misaligned with the rationalistic assumptions underpinning the WLC concept. This provides a possible explanation for why few successful implementations of the concept have been presented in literature.     

Editorial Another milestone

A Master Production Scheduling Decision Support System within a multi-product medical supplies market has the dual task of providing good customer service levels while maintaining minimum reasonable levels of finished goods stock in the face of considerable internal manufacturing lead time and customer demand uncertainty. This paper examines the critical design parameters within an adaptive model highlighting how the total system orders in the internal pipeline are utilized in the decision-making process for assessing how much to load the internal manufacturing pipeline. Two different methods for tracking manufacturing lead times within the adaptive loop are also considered. Classical control concepts are applied within the Decision Support System (DSS) to avoid any long-term drift in finished stocks. Finally scenario analysis is performed via simulation for a set of design parameters and a range of stimuli typical of company operating situations. An effective decision support system design in terms of architecture and parameter settings is recommended based upon the ability of the model to maintain high customer service levels. The DSS readily interfaces between marketing and production functions to enhance company competitive advantage across a wide range of products.     

Obtaining the optimal fleet mix: A case study about towing tractors at airports

Planes do not have a reverse gear. Hence, they need to be towed by tractors when leaving the gate. Towing tractors differ with respect to investment as well as variable costs and plane type compatibility. We propose a model which addresses the problem of a cost minimal fleet composition to support towing service providers in their strategic investment decisions. The model takes into account a maximum lifetime, a minimum duration of use, an overhaul option and a sell option. In a case study with a major European airport (our cooperating airport) we generate a multi-period fleet investment schedule. Furthermore, we introduce a 4-step approach for demand aggregation based on flight schedule information. We analyze the impact of demand variation, flight schedule disruptions and cost structure on the optimal buy, overhaul and sell policy. The scenario analyses demonstrate the robustness of the investment schedule with respect to these factors. Ignoring the existing fleet, a green field scenario reveals saving potentials of more than 5% when applying this model.     

Hierarchical production planning at a multiproduct multiprocessor fibreglass manufacturing facility

Abstract

Abstract. A hierarchical production planning model is developed for a forming facility of a major fibreglass manufacturer. The model establishes aggregate quarterly quantities for families of products, monthly disaggregate production quantities for end-items within these families, and a weekly sequencing schedule of end-items. A key feature of the planning system is its ability to decompose total set-up cost into primary and secondary components and to account appropriately for each component at a distinct level of the planning hierarchy. The mathematical programming formulations, the accompanying solution algorithms, and the results of their application to nine months of actual company demand and cost data are presented.     

CHANGING MANUFACTURING STRATEGY

This paper demonstrates an approach to successfully managing change of manufacturing strategy. It first introduces the issues and management guidelines, and then describes how one company used this approach to achieve dramatic benefits from changing its manufacturing strategy. A third part of the paper elaborates on how the company made the approach work.     

Aligning manufacturing strategy and levels of automation: A case study

Research has shown that alignment between manufacturing strategy and decisions regarding automation are often of an ad hoc nature, i.e. the support for automation decisions is poor. Support tools to find an appropriate level of automation are thus needed in order to achieve more efficient and robust production systems. The methodology presented in this paper contains five sub-processes where the chosen level of automation is aligned with the manufacturing strategy. Together they form an automation strategy, which secures a desired direction of the firm and also supports robustness and reliability of the manufacturing system due to the holistic approach chosen.