Short-term Production Planning Research Articles

Implementing new dispatching rules at SGS-Thomson Microelectronics

This paper reports a real-life manufacturing case study in the short term production planning and control for a very large scale integrated (VLSI) circuit manufacturing production unit Dispatching in VLSI manufacturing is a crucial issue, since often binding constraints are set on the delivery dates by the customers downstream in the supply chain, while manufacturers , due to the huge fixed cost of capital goods, must ensure the full utilization of their shop floors. The complexity of the manufacturing technology and the re-entrant nature of the resulting production flows further add difficulties to the problem. Starting from a shop floor scheduling based on simple dispatching rules, e.g. FIFO rule, or the well-known 'minimum set-up' criterion, workcentres have been firstly grouped according to their nature, then they have been classified according to their criticality in terms of production capacity and flexibility. Finally, for each class, a customized, yet suitable to be implemented, dispatching rule is proposed and tested through a wide simulation campaign. Experimental results show that the proposed dispatching approach leads to a superior overall output and, at the same time, to an increased delivery timeliness.

Resource-free and resource-dependent aspects of process modelling: A rule-based conceptual approach

The Esprit project 8224-RUMS a RUle-based Manufacturing Modelling System is aimed at providing small-medium enterprises with advanced software tools supporting product design, process design and long-, medium- and short-term production planning. Process modelling constitutes a critical point of the project, since it links product structure to planning functions. A new process representation has been introduced that overcomes limitations of current techniques, e.g. inability to model products as belonging to generalized families, or request of burden amounts of data to manage. The proposed approach is based on a neat separation between abstract resource-free definitions of manufacturing operations and actual resourcedependent specifications of set-up and operational conditions and times. Following this solution, most of the aspects of process modelling can be expressed as rules. Rules provide a concise representation that avoids redundancies and enables computer-based knowledge control and processing.

Conditional LAS stochastic simulation of regionalized variables in random fields

Ore reserves forecasts are required to aid in investment decisions, mine design and valuation, short and long term production plans and proper and efficient mill design. In random multivariable fields with limited data and high levels of uncertainty, the kriged block estimates produce a smoothing effect resulting in underestimating high values and overestimating low values. The modified conditional simulation (MCS) methodology solves these problems by simulating the random field to preserve its mean and the variance structure. The simulation model is conditioned to reproduce the data at known sample points to minimize the variability between the simulated data and the true field data. In this study, the authors develop the MCS methodology to simulate ore reserve grades using the best linear unbiased estimation (BLUE) and the local average subdivision (LAS) techniques. The MCS methodology is applied to simulate block grades in a section of the Sabi Gold Project in Zimbabwe. The results are compared with the kriged estimates for this section. Analysis of the results shows that the MCS methodology reproduces the known sample grades with minimum estimation error of 0.001 while the estimation error associated with the kriged estimates is 1.104, a 100% efficiency of the MCS method over the kriging technique.

Demand shuffle—A method for multilevel proportional lot sizing and scheduling

This contribution acquaints the reader with a model for multilevel single-machine proportional lot sizing and scheduling problems (PLSPs) that appear in the scope of short-term production planning. It is one of the first articles that deals with dynamic capacitated multilevel lot sizing and scheduling, which is of great practical importance. The PLSP model refines well-known mixed-integer programming formulations for dynamic capacitated lot sizing and scheduling as, for instance, the DLSP or the CSLP. A special emphasis is given on a new method called demand shuffle to solve multilevel PLSP instances efficiently but suboptimally. Although the basic idea is very simple, it becomes clear that in the presence of precedence and capacity constraints many nontrivial details are to be concerned. Computational studies show that the presented approach decidedly improves recent results. © 1997 John Wiley & Sons, Inc. Naval Research Logistics 44: 319–340, 1997

Demand shuffle?A method for multilevel proportional lot sizing and scheduling

This contribution acquaints the reader with a model for multilevel single-machine proportional lot sizing and scheduling problems (PLSPs) that appear in the scope of short-term production planning. It is one of the first articles that deals with dynamic capacitated multilevel lot sizing and scheduling, which is of great practical importance. The PLSP model refines well-known mixed-integer programming formulations for dynamic capacitated lot sizing and scheduling as, for instance, the DLSP or the CSLP. A special emphasis is given on a new method called demand shuffle to solve multilevel PLSP instances efficiently but suboptimally. Although the basic idea is very simple, it becomes clear that in the presence of precedence and capacity constraints many nontrivial details are to be concerned. Computational studies show that the presented approach decidedly improves recent results.

Integrating intelligent job-scheduling into a real-world production-scheduling system

The paper addresses the problem of scheduling production orders (jobs). First, an approach based on simulated annealing and Hopfield nets is described. Since performance was unsatisfactory for real-world applications, we changed the problem representation and tuned the scheduling method, dropping features of the Hopfield net and retaining simulated annealing. Both computing time and solution quality were significantly improved. The scheduling method was then integrated into a software system for short-term production planning and control (‘electronic leitstand’). The paper describes how real-world requirements are met, and how the scheduling method interacts with the leitstand's database and graphical representation of schedules.

Synthesis of flexible and reliable short-term batch production plans

This paper considers the definition and evaluation of flexibility and reliability indices for short-term batch plant operation schedules. A deterministic flexibility metric ( F), a stochastic flexibility metric (SF) and a stochastic reliability metric (SR) are defined in a form that is compatible with uniform discretization time MILP models. The stochastic metrics can be combined to form a single SRF index, quantifying the probability of successfully dealing with the expected uncertainty in both the operating parameters and in the availability of processing equipment. In what concerns reliability analysis, the approach exploits the task network representation of batch operation plans. Thus, the estimation of the reliability of an operation plan can be transformed into the evaluation of the reliability of an associated network, which can then be established by one of several known techniques.

Distributed Artificial Intelligence in manufacturing systems control

This research uses a Distributed Artificial Intelligence (DAI) framework to efficiently utilize the infrastructure available for process planning in a batch processing PWB assembly facility. The DAI approach decomposes the entire production control task into several sub-tasks. Then, the sub-tasks are implemented by the basic elements of the DAI system called ‘intelligent agents’. By working collectively, the intelligent agents of the DAI system can arrive at a solution for the problem. The DAI system initially proposes all possible solutions generated by the intelligent agents. Then, a fuzzy coordination technique is utilized to evaluate the solutions and to find the most appropriate one for shopfloor implementation. Using inputs such as the short-term production plan, design data, shopfloor observation data, and CAD information, the DAI system provides applicable production plans with ranks for the feasibility of current assembly activities.

Using the virtual cell concept for short-term production planning for flexible job shop manufacturing systems

Abstract Short-term production planning (STPP) problems in flexible job shop manufacturing systems (FJSMS), which consist of computerized numerically, controlled (CNC) machines and dedicated machines, are discussed here. Short-term production planning problems of FJSMS include part type selection, process selection, batch sizing and part family/ machine group formation. A proposed STPP system for FJSMS is developed for cases where production contents are frequently changed thus resulting in the physical machine layout being not justified. It mainly adopts a restricted-period planning approach, using a virtual cell's concept for solving the STPP problem. The planning goal of STPP is to satisfy quantity and due date requirements as determined by MRP/CRP, with due consideration to the features of NC machines and dedicated machines.

The Application of Intelligent Controllers in the Automation of a Small Plant for Recycling of Secondary Polymers

Abstract An intelligent system for integral management of a small plant for recycling of secondary polymers has been developed. The system uses intelligent regulators with wide functional potentialities that can meet the peculiarities of the this type of enterprises, such as vast and frequent changes of operative conditions. The developed regulators include functions on short-term production planning, steady-state optimizationof the separate units, optimization of the nonstationary regimes of the most important technological parameters. Combination of model-based and fuzzy reasoning based methods for choosing optimal static regimes and gain-scheduling technique in controlling modified standard regulators has been accomplished. Data for experimentally obtained characteristics of the basic units of a small plant and the results of the simulation research work are adduced. The peculiarities of the realizations of the basis of PC and industrial controllers are studied.

A flexible approach to part type selection in flexible flow systems using part mix ratios

The short-term production planning function for setting up a flexible manufacturing system (FMS) prior to production should be developed so as to interact well with the operation of the system over time. During FMS operation, planning for system set-up has to be performed somewhat periodically, for example, when the part mix is changed, or when the production requirements are finished for some part types, or when a machine breaks down. Since all cutting tools required for all part types that need to be machined cannot usually fit in the machines' limited capacity tool magazines, decisions need to be made concerning which part types will be produced next. This paper suggests a more flexible approach than is typical for short-term production planning. The differences between the proposed flexible approach and previous approaches taken in the literature and in industry to solve these problems are provided. A description of when either a batching or a flexible approach is appropriate is provided. An existing mathematical programming procedure that determines balanced (or unbalanced) part mix ratios for part types to balance machine workloads is adapted to solve another planning problem of selecting part types to be machined together over the upcoming time period. A simulation model is developed to demonstrate the implementation of both the suggested flexible approach and batching on a realistic flexible flow system (FFS) having pooled machines of unequal sizes. The research results indicate that: (1) the flexible approach usually leads to better system utilization and makespan than batching; (2) using the flexible approach enables the system to be utilized more constantly; and (3) the flexible approach requires fewer fixtures dedicated to particular part types than batching to complete the production requirements of all part times. Computational results are presented to demonstrate the performance of the part type selection approaches. Further research needs are also discussed.

A short term production planning and scheduling model

An optimal decision making model is developed to assist the manufacturer to select among the potential customer orders, which orders to reject and which orders to accept and in what quantities such that the net operational profit during the planning time horizon will be maximized. This model is developed based on the group technology concept and assumes that (i) job splitting is allowed, (ii) all the necessary stages of operation of each job (e.g., a batch of identical parts with a specified due date, availability time, required setup time, and required processing time) at each workstation (e.g., assembly cell) is represented by a single aggregated stage of operation, (iii) the time horizon is set to be sufficiently short, and (iv) the processing priorities of the potential customer orders during the planning time horizon is specified. Based on the above model, an operational plan for optimal loading of an integrated manufacturing system consisting of a set of finite capacity workstations linked by a material handling system is obtained.

Extended Applications of Simulation in Manufacturing Systems

The way we perceive CIM (Computer Integrated Manufacturing) is described for giving the necessary insight and understanding of the complexity. It is generally accepted that simulation is a powerful tool in planning and design of manufacturing production systems. But simulation has even larger potentials as an integral part of the computerized factory. The research is carried out along two lines: 1: Simulation as an integral part of the information system for short and long term production planning. In the field of simulation as a real time planning tool, simulation has been integrated with generative process planning and other integrations with e.g. MRP systems, control computers, databases etc. are under consideration. 2: Simulation used as a tool for developing control software for FMS, and software for the dispositive control of FMS. Simulation can be advantageous in test and design of the software through determination of the logic structure before implementation.

A Simulation Analysis of a Reserve Stock Management Policy for Feed Grains and Wheat

During the last three years agriculture has exhibited characteristics that parallel those of a manic depressive. The livestock sector was flying high during 1973 and in the depths of despair in 1974. The crop sector was elevated from two decades of despondent but stable economic health to a state of price elation in 1973 and 1974. Over the last couple of years consumers, who enjoyed excellent food budget health for years, have slipped into a state of belligerent depression. Each group views the future with anxious dismay. Livestock producers fear that the feed prices will remain high, crop producers fear they will not. Neither livestock nor crop producers have a sound basis for making short or longer term production plans.