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Performance improvement for requirements planning systems is an issue which receives wide interest. Many programming approaches have been proposed to improve material requirements planning procedures. However, most of them appear to be too complex for large manufacturing problems. Alternatively it might be promising to explore the integration of materials requirements planning and capacity requirements planning. Several simple heuristics for integrated requirements planning systems are suggested. Several heuristics are offered to balance the load in the systems and several procedures presented to adjust the planned requirements so that the system will execute more smoothly. An industrial example supports the adequacy of the general concepts provided in this research. Results are presented which demonstrate the adequacy of these heuristics, and illustrate the ease of implementing the procedures into any MRP system.

A comprehensive review of the literature for the problem of lot‐size scheduling (serial and assembly) considering the uncapacitated problem and complicated capacitated assembly manufacturing structure. Analyses the different solution techniques and findings for each product set.

Concentrates on two key aspects of manufacturing resource planning (MRPII) theory and design, namely; how master production scheduling is carried out in differing business environments and how well the “closing of the loop” operates by checking the capacity requirements of the different levels of plans within an organization. The methodology involved detailed investigations into master scheduling and capacity planning in eight diverse manufacturing companies. This was followed by a nationwide survey of users, a survey of all the major suppliers of production management software in the UK and an analysis of the facilities offered by current software packages. The main conclusion which is drawn is that in the majority of companies, only just over 50 per cent are attempting resource and capacity planning and only 20 per cent are successfully feeding back capacity requirements planning (CRP) information to “close the loop”. Various causative factors are put forward and remedies are suggested.

The purpose of this paper is to explore different aggregate production planning (APP) strategies (inventory levelling, validation of the workforce and flexible production alternatives: overtime and/or outsourcing) by using a system dynamics model in a two-level, multi-product, multi-period manpower intensive supply chain (SC). Therefore, the appropriateness of using systems dynamics as a research method, by focusing on managerial applications, to analyse APP policies is proven. From the combination of systems dynamics and APP, recommendations and action strategies are considered for each scenario to understand how the system performs and to improve decision making on APP in the SC context.

The research design analyses a typical factory setting with representative parameter settings for five different conventional APP policies – inventory levelling, workforce variation, overtime, outsourcing and a combination of overtime and outsourcing – through deterministic systems dynamics-based simulation. In order to validate the simulation model, the results from published APP models were replicated. Then, optimisation is conducted for this deterministic setting to determine the performance of all these typical policies with optimal parameter settings. Next, a Monte Carlo stochastic simulation is used to assess the robustness of such performances in a variety of demand settings. Different aggregate plans are tested and the effect that events like demand variability and production times have on the SC performance results is analysed.

The results support the assertion that the greater the demand variability, the higher the flexibility costs (overtime, outsourcing, inventory levelling, and contracts and firings). As greater inter-month oscillations appear, which must be covered with additional alternatives, the optimum number of employees must be determined by analysing the interchanges and marginal costs between capacity oversizing costs (wages, idle time, storage) and the costs to undersize it (penalties for lowering safety stocks, delayed demand, greater use of overtime and outsourcing). Accordingly, controlling the times to avoid increased costs and penalties incurred by delayed demand becomes an essential important task, but one that also depends on the characteristics of this variability.

This paper has developed a modelling approach for APP in a manpower intensive SC by applying system dynamics. It includes a simulation model, the analysis of several scenarios, the impact on performance caused by variability events in the parameters, and some recommendations and action strategies to be subsequently applied. The modelling methodology proposed can be employed to design-specific models for each SC.

This paper proposes an APP system dynamics approach in a two-level, multi-product, multi-period manpower intensive SC for the first time. This model bridges the gap in the literature relating to simulation, specifically system dynamics and its application for APP. The paper also provides a qualitative description of the various pros and cons of each analysed policy and how they can be combined.

The applicability of manufacturing planning and control methods differs between environments. This paper explains the fit between the planning environment and material and capacity planning on the detailed material planning and shop‐floor planning levels. The study is based on a conceptual discussion and a survey of 84 Swedish manufacturing companies. Results show the use of planning methods and their levels of user satisfaction in complex customer order production, configure to order production, batch production of standardized products and repetitive mass production, respectively.

This paper presents the results of a panel of experts, made up of academics in the field of operations and supply chain management, enterprise requirement planning software developers, and end‐users, whose work has aimed at defining the main features that characterize an enterprise modeller for the fashion industry. The characteristics required by the enterprise requirement planning enterprise modeller have been identified, with specific attention to the production planning and control module. Because of the peculiarities of this line of business, it is widely recognized that both vendors and buyers would benefit from such a tool. For the formers, the availability of a pre‐customized reference model would represent a competitive advantage in the marketplace, for the latter, on the other hand, it would enhance the effectiveness, the efficiency and the likelihood of success of the enterprise requirement planning implementation project.

Reports the development and successful implementation of a computer‐integrated production and operations management system (POM), encompassing schedule activities such as aggregate production plan, master production schedule and material requirements plan, and capacity activities such as financial plan, resource requirements plan, rough‐cut capacity plan and capacity requirements plan, at the planning level. POM’s icon‐menu driven system which associates icons with decision model spreadsheets makes it very user‐friendly, and facilitates the integration of decisions encountered by industrial/ manufacturing engineers and operations managers.

Addresses the problem of implementing just‐in‐time (JIT) principles in a processing shop organized in a batch manufacturing environment. The focus is on a processing shop separated from an assembly shop by a parts store. Presents a multi‐criteria variant of the capacitated lot‐sizing model. The approach involves a pre‐emptive priority for JIT processing schedules, and a secondary priority for desirable load profiles. Solution properties are derived and used to facilitate the solution process for both the primary and secondary criterion models. Load profiles are assessed in the context of capacity requirements planning as well as from the alternative viewpoint of providing feedback to capacity planning through a consideration of capacity cushions. At both planning levels the approach is shown to allow optimum resource utilization without violating JIT principles. Presents optimization procedures, including a heuristic with an analytic performance bound.

Based on detailed analysis of seven case studies, involving consideration of approximately 300 parameters and face to face interviews with senior managers, identifies key characteristics which should be taken into account during the selection and effective implementation of different types of manufacturing control systems in individual manufacturing environments. These key characteristics help identify the need for particular functions of manufacturing control systems, as well as the impact on effective implementation and operation. They are grouped under the headings of complexity, uncertainty and flexibility. Concludes with a discussion of a structured approach which may be used to take account of key characteristics during the selection of a manufacturing control system.

Versatile manufacturing (VM) companies typically manufacture high variety, mainly customised products in relatively low volumes, competing for each order with other supplier companies on the basis of price, technical expertise, delivery time and punctuality. The research presented in this study is included in a wide cross‐disciplinary project which involved seven research centres. In particular, this paper aims at identifying the general requirements and guidelines for the definition of an integrated model of the order to delivery cycle in a VM environment, which can particularly be suitable for the small‐medium enterprise needs. A number of guidelines emerged, mainly in the areas of customer requirements definition and commercial configuration of customer order, supply and production planning, and intermediate and final project evaluation.