An effective part-selection model for production planning of flexible manufacturing systems

This paper presents an integer programming model for existing FMS users to select the most cost effective set of parts to run simultaneously on an FMS during a specified production horizon. Two heuristic solution algorithms are developed by dividing the part-selection procedure in two stages. One stage deals strictly with the limitations on machining time, storage capacity, and AGV time. For the other stage, three different stages are used to choose a set of pan solely based on tooling and fixture constraints. The best algorithm-strategy combination has been identified and proved to be very efficient in finding optimal or near optimal solutions.     

A production planning model for cellular manufacturing systems with refixturing considerations

In this paper we consider the problem of assigning operations of part types to one or more machines in a cellular manufacturing system. We develop a mixed integer linear model considering trade-off between refixturing and material handling movement. Examples are included to illustrate the applications of the models developed.     

Grouping parts and tools in flexible manufacturing systems production planning

Batch production in a flexible manufacturing environment is necessary not only to satisfy some technological constraints but also to achieve potential reductions in processing time, to reduce work-in-process and finished goods inventories, and to simplify the production planning process. Central to batch production is the problem of grouping part types and the required tools into families for simultaneous processing. This paper presents a practical and useful algorithm for grouping parts and tools in flexible manufacturing systems (FMSs).This problem is first formulated as a 0-1 linear integer program. A Lagrangian dual formulation is then developed to obtain an upper bound on the optimal objective function value. The Lagrangian dual program is further decomposed into a linear network subproblem and a set of knapsack subproblems. A subgradient algorithm with several enhancement strategies is employed to minimize the upper bound obtained from the dual problem. Computational results for medium and large-scale problems demonstrate that this solution procedure is effective.     

Multi-objective cell formation and production planning in dynamic virtual cellular manufacturing systems

This article presents a fuzzy goal programming-based approach for solving a multi-objective mathematical model of cell formation problem and production planning in a dynamic virtual cellular manufacturing system. In a dynamic environment, the product mix and part demand change over a planning horizon decomposed into several time periods. Thus, the cell formation done for one period may be no longer efficient for subsequent periods and hence reconfiguration of cells is required. Due to the variation of demand and necessity of reconfiguration of cells, the virtual cellular manufacturing (VCM) concept has been proposed by researchers to utilise the benefits of cellular manufacturing without reconfiguration charges. In a VCM system, machines, parts and workers are temporarily grouped for one period during which machines and workers of a group dedicatedly serve the parts of that group. The only difference of VCM with a real CM is that machines of the same group are not necessarily brought to a physical proximity in VCM. The virtual cells are created periodically depending on changes in demand volumes and mix, as new parts accumulate during a planning horizon. The major advantage of the proposed model is the consideration of demand and part mix variation over a multi-period planning horizon with worker flexibility. The aim is to minimise holding cost, backorder cost and exceptional elements in a cubic space of machine–part–worker incidence matrix. To illustrate the applicability of the proposed model, an example has been solved and computational results are presented.     

A method for comparing flexibility performance for the lifecycle of manufacturing systems under capacity planning constraints

The objective of this work is to describe a method for comparing the flexibility performance of manufacturing systems, in an uncertain environment, under lifecycle considerations and capacity planning constraints. The manufacturing systems costs are estimated over a time horizon and for a large variety of possible market scenarios. In order for the lifecycle cost values to be comparable among different systems, their values are calculated with the use of a special purpose algorithm. Statistical analysis of the estimated cost values is then employed for assessing the flexibility of each manufacturing system. The method is applied in an industrial case for checking, also from a flexibility point of view, the investment on a production system, using real life industrial data.     

A review on strategic capacity planning for the semiconductor manufacturing industry

Due to the high capital investment cost in the semiconductor manufacturing industry, strategic capacity planning plays an important role in improving business performance. The reasons that make these problems especially difficult are: the complex fabrication process, rapid changes in technology and products, the long lead time and the high cost of capacity increment, and the high uncertain demand and capacity. Hence, a review of the existing solutions to capacity planning to cope with these difficulties is important for developing new methodologies and practices. In this paper, we provide a review of the current research and fundamental methods in strategic capacity planning, identify emerging methods for capacity planning, and take an in-depth look at future research interests.     

A method for the hierarchical planning of the structure,dimension and material requirements of manufacturing systems

Growing competition creates pressure among companies to run their production in a cost-optimal way and yet adapt immediately to changes in their environmental conditions. Decisions must always consider the integration of the companies in globalised markets on both the demand and supply side. This paper deals with the optimal planning of decisions concerning the structure and dimension of production facilities. The methods used for material requirements planning are selected and configured according to these decisions. These decision problems are represented in the form of four hierarchically layered partial models, each of them realised and iteratively solved by a mathematical optimisation model. The hierarchical planning method is evaluated using a practical case example based on a valve production system of a manufacturing company.     

Production planning for flexible manufacturing systems with multiple machine types: A practical method

We study three important production planning problems for flexible manufacturing systems (FMSs) that consist of multiple types of machines. Namely we address machine grouping, workload allocation among machine groups, and batch sizing that maximize system throughput, when part types are selected for the upcoming production period. This differs from earlier related works in that earlier works give either only qualitative characteristics of the optimum solution or provide a solution method for FMSs consisting of only one type of flexible machine. In this paper, we provide both the optimum and heuristic methods to simultaneously solve the three problems for realistic FMSs. Computational results show that the heuristic method always finds the optimum solution at a fraction of computation time and that batch sizing can significantly affect throughput. Development of the heuristic method is necessary since the optimum method can be time-consuming for a moderate size of problems.     

Semi-heterarchical production planning structures in the support of team-based manufacturing

Manufacturing enterprises are facing fierce competition within the modern global market, resulting in a requirement for continuous improvement of their production management practices. In this context, a number of manufacturing paradigms such as team-based manufacturing have been adopted to provide the flexibility, agility and responsiveness required to cope with the volatility of production demands. The introduction of team-based working practices necessitates a clear definition and delegation of responsibilities to various teams and often requires significant changes in production planning and control procedures. The successful implementation of such a distributed production approach is then dependent on the way that the production teams manage their internal activities and cooperate with other teams to achieve overall manufacturing goals. A novel team-based distributed production planning and control approach based on a semi-heterarchical structure is presented that aims to support the autonomous and cooperative attributes of various production teams within manufacturing enterprises.     

Material requirements planning in hierarchical production planning systems

Material requirements planning (MRP) is a way to develop the time phased material and other resource requirements to satisfy the needs of a master production schedule. Hierarchical production planning (HPP) is a framework for analysis and decision making in complex production environments. They are complementary approaches to the decision support system needs of multi-stage production systems. The hierarchical approach provides for efficient management review of proposed plans at corporate, plant, and shop levels while MRP provides a sound and detailed basis for understanding the implications of proposed plans and for executing the selected plan. The relationships between these two approaches are illustrated with an example application.     

Parts-mix analysis in recycling-oriented manufacturing systems for multiple-item production

One solution to environmental problems is to construct a recycling-oriented manufacturing system, in which waste products after consumption are collected, and reusable parts in the collected products are employed to produce new products. A parts-mix in the manufacturing system for multiple-item production is analysed by taking into consideration the merits and demerits of the usage of common parts over multiple products and special parts utilized for individual products. The parts-mix problem is formulated to minimize the life-cycle cost, which consists of production costs and recycling costs. The property of the optimal parts-mix is clarified, and a decision procedure to solve the parts-mix is developed. The procedure decides whether the common parts are effective or not.     

The fit of planning methods for the part manufacturing industry,a case study

This paper investigates the specific planning environment of an automotive part manufacturer and characterizes this environment based on variables regarding the product,its demand and the manufacturing process.The fit of different planning methods,namely material requirements planning,reorder point,cyclic planning,kanban,and heijunka to this specific planning environment is analyzed and evaluated by exploratory research.The results show that different product characteristics make it hard to apply a single planning method.None of the investigated methods show the ability to cover the complex requirements of a combined planning environment of two partly divergent product types with a deep value chain.     

Integrated production planning and quality control for linear production systems under uncertainties of cycle time and finished product quality

This work considers serial production systems with several process steps and a possible quality control at final step. It deals with the problem of optimising planned lead time when the real lead time for each process is stochastic and the finished product quality is uncertain unless it is inspected. Three analytical models are proposed aiming to minimise the expected total cost, which is composed of the inventory and backlogging costs for the finished product and quality costs associated with inspection and non-conformities. These models correspond to three quality control policies: (i) without quality control, (ii) with quality control but without taking into account the inspection duration when optimising the planned lead time and (iii) with quality control and with considering the inspection duration when optimising the planned lead time. Based on the results, it can be highlighted the economic advantage of integrating quality control at the early stage of supply and production planning decisions for some cost parameters conditions. The robustness of the proposed models is also analysed regarding the variance of the probability distributions of the lead times.     

Machine cell formation for production management in cellular manufacturing systems

The formation of machine-part families is an important task in the design of cellular manufacturing systems. Manufacturing cell grouping has the effect of reducing material handing cost and work in process. Among the many methods utilized in machine cells formation, the similarity coefficient method is most widely used. Production sequence and product volumes, if incorporated properly in determining the machine cells, can enhance the quality of solutions and reduce the number of intercellular movements. Measures for cell formation based on operations sequence utilizing ordinal production data are few and have many limitations, such as counting the number of the trips for each individual part instead of counting the weights of the batches. A new ordinal production data similarity coefficient based on the sequence of operations and the batch size of the parts is introduced. Furthermore, a new clustering algorithm for machine cell formation is proposed. The new similarity measure showed more sensitivity to the intercellular movements and the clustering algorithm showed better machine grouping.     

Machine-component group formation: an heuristic method for flexible production cells and flexible manufacturing systems

This paper provides an heuristic for the planning and study of machine-component groups in flexible production cells and flexible manufacturing systems. The problem of group formation defined on master-component process routes is undertaken in terms of minimum differences between masters and maximum combinations of masters. Group formation is a ‘hard’ combinatorial problem subject to exponential growth of complexity as the number of decision-making variables increases. The heuristic is designed to search the solution space of the problem in monotone-increasing order of solution costs so as to avoid the enumeration of solutions for cost minimization.     

Flexible design of production planning systems

The paper discusses future production systems with emphasis on new production management concepts. Planning problems are identified. Computer applications in the fields are briefly explained. The main part of the paper discusses basic operations in production management. These are operations invariant to different applications and will thus serve as truly modular building blocks in a computer based production management system. The data structures involved are discussed and a list of operations proposed.     

Socio-technical organization of cell manufacturing and production islands in the metal manufacturing industry in Germany and the USA

I report on research conducted on the US and German metal manufacturing industry. It examines recent changes in technology and work organization: cell manufacturing in USA, and production islands in Germany. The argument will be made that under considerable external pressure to change, the focus of response is on work organization rather than technology, with similar problems occurring. A particular problem in each country is the lack of job rotation both within and between cells and production islands, and the presence of an incentive pay system whose goals lack compatibility with the tenets of the new manufacturing environment. While in both countries, there is considerable experimentation with new forms of work organization, the German approach tends to be more steady with slower change, whereas in the USA change has been rapid with major consequences for unions. The latter part of the paper deals much with industrial relations.     

A multi-objective production planning model in a flexible manufacturing environment

Production planning for flexible manufacturing systems (FMS) has been studied using different methods, including simulation; queueing networks; and several single-objective mathematical programming techniques. The decision making process for production planning in FMS usually involves multiple conflicting objectives. Thus, goal programming (GP) can be effectively applied to this decision problem. This study discusses the superior aspects of the GP model over other models, when solving the production planning problem for FMS. A GP model is presented and the implementation results of an illustrative problem are analysed.     

A new heuristic for integrated process planning and scheduling in reconfigurable manufacturing systems

Integrated process planning and scheduling (IPPS) is a manufacturing strategy that considers process planning and scheduling as an integrated function rather than two separated functions performed sequentially. In this paper, we propose a new heuristic to IPPS problem for reconfigurable manufacturing systems (RMS). An RMS consists mainly of reconfigurable machine tools (RMTs), each with multiple configurations, and can perform different operations with different capacities. The proposed heuristic takes into account the multi-configuration nature of machines to integrate both process planning and scheduling. To illustrate the applicability and the efficiency of the proposed heuristic, a numerical example is presented where the heuristic is compared to a classical sequential process planning and scheduling strategy using a discrete-event simulation framework. The results show an advantage of the proposed heuristic over the sequential process planning and scheduling strategy.