A sequential method for the development of visual interactive meta-simulation models using neural networks

This paper proposes a practical and efficient method for the development of visual interactive meta-simulation models using neural networks. The method first uses a randomised simulation experimental design to obtain a set of results from a previously validated simulation model. The bootstrap technique is used on these results to generate a series of neural network models that are then trained using back propagation. The visual interactive meta-simulation model consists of the collective response from the trained neural network models. The accuracy of the meta-simulation model is assessed using the bootstrap technique and improved accuracy obtained by increasing the size of the randomised simulation experimental design set and re-training. This paper describes the approach, gives results for five example problems and suggests that the method is a practical extension to visual interactive simulation.     

分享经济环境下制造业产能分享的三群体演化博弈分析

制造业产能分享的兴起,改变了传统的制造模式,打破了原有制造业系统的平衡。为研究制造业产能分享参与群体的决策行为,在产能分享平台具有网络外部性、制造企业具有接入成本且博弈群体均具有有限理性的假设条件下,构建了“产能分享平台-制造业产能所有企业-制造业产能需求企业”三个博弈群体的演化博弈模型。运用演化博弈理论分析了模型的演化稳定策略,探讨了制造企业接入成本、产能分享平台的网络外部性系数等对此动态系统稳定性的影响,给出了演化稳定策略的经济和管理意义。最后,用数值仿真对比分析不同参数变化对演化结果的影响,为产能分享平台和制造企业的行为决策提供理论参考依据。     

The Interactive Development of Visual Simulation Models

Visual interactive simulation has been shown to have advantages over conventional ‘batch’ simulation. This paper suggests that further gains could be made by providing the facilities necessary for the interactive development of such models. An experimental system is described which embodies some of these facilities.     

Mathematical Modeling of Multilayer Filters for Telecommunication

The article presents an interactive approach to the design of Wavelength Division Multiplexing (WDM) filters that combines classical design methods for multi-resonator systems with a semi-heuristic integer optimization method. This approach proves to be exceptionally efficient from the computational point of view and generates a whole range of different filter designs with virtually equivalent spectral properties. The article also considers a method for analyzing the sensitivity of WDM filters to manufacturing errors. The sensitivity analysis relies on computer simulation of thin-layer coating with optical monitoring of layer thickness by the turning point method. This analysis enables the designer to assess alternative filter designs with the purpose of improving manufacturing efficiency.     

Forecast frequency in rolling horizon hedging heuristics for capacity expansion

This paper describes a simulation study of the effect of forecast revisions and hedges against demand uncertainty in a rolling horizon heuristic for capacity expansion. The model is based on data collected in the utilities division of a large chemical manufacturing plant. A seasonal integrated moving average model for the demand is used to generate forecasts, while capacity additions are determined by applying a simple timing rule to various hedges around the forecast. The simulation results indicate that hedging forecasts by their prediction limits rather than a fixed buffer significantly reduces undercapacity at the expense of a small increase in capacity cost. The prediction limit hedge is more robust to delays in reforecasting.     

Strategic capacity planning for light emitting diode (LED) supply chains across Taiwan and China

This paper describes a mixed-integer programming (MIP) model formulated for strategic capacity planning for light emitting diode (LED) makers of Taiwan, major companies in the global LED market. These firms have complex supply chains across Taiwan and China, and the region’s unique political and economic environment has created not only competitive advantages but also challenges in supply chain management: government regulations require that customer orders be accepted from Taiwan or China according to customer attributes; when conducting manufacturing, Taiwanese firms may need to transfer orders across national borders for reasons such as manufacturing technology (the required technology is available only at certain manufacturing facilities) or more efficient capacity utilization; and there are operations to be performed with specific processing requirements to follow, posing substantial challenges for planners. Motivated by the significance of these firms in the global market, we develop a MIP model with novel features to support their strategic capacity planning, covering demand and manufacturing-related decisions, including order acceptance and transfer, manufacturing starts, capacity expansion, and logistics. We illustrate the model’s performance using modified industry data in a numerical example; we also describe the potential impacts the model may create in industry applications.     

Rapid and modular prototyping-based Petri nets and distributed simulation for manufacturing systems

This paper presents an approach to simulate and implement by stepwise refinement the whole manufacturing system (MS) by means of distributed simulation. This approach is based on the use of different classes of Petri nets to model different levels of a manufacturing system. Furthermore these classes may match the abstraction levels of a high-level Petri net used to model the MS. Each level can be simulated on a processor or a cluster of processors which can communicate between themselves using a network. The main contribution is to give the opportunity to combine simulation, performance evaluation and emulation. The emulation means that a part of the system can be run in real time while the other part is simulated. Moreover based on the abstraction levels of high-level Petri nets, subsystems can be integrated step-by-step from the design stage to the implementation one, allowing inter-changeability between simulated components and real-time physical systems. This approach is achieved by defining a simulation engine which involves a local simulator, an emulator and an interface to the physical process. Criteria are defined to use an emulator or a local control software for a physical process as a logical process for the conservative distributed simulation.     

Evaluating capacity management tactics for a legacy manufacturing plant

Robust capacity improvement tactics, namely acquisition of assets and enhanced flexibility in product manufacturing, that alleviate mismatches between required and available capacity are revealed by data analytics. Improvement brought about by these tactics as measured by two performance metrics, production makespan and product availability, is assessed using optimization methodology. This paper demonstrates the value of analysing demand and product specification data to inform capacity re-calibration in an S&P 500 company in the chemical industry. The tactic recommended for implementation, which yielded up to a doubling of the capacity, emerged from an empirical analysis of data for five prototypical planning periods.     

Protective capacity positioning: Impact on manufacturing cell performance

Protective capacity is the `extra' capacity placed at non-bottleneck resources to absorb random disruptions in planned levels of performance so that the bottleneck resource is more effectively utilized. Although informative, the research related to protective capacity offers little insight into the preferred placement of protective capacity. By building on the existing research, our study develops hypotheses related to protective capacity positioning and then tested them by using a simulation model of a manufacturing cell. The results indicate that the placement of the protective capacity has no practical influence on mean flow time, but it strongly influences bottleneck shiftiness. Specifically, the study's results may indicate that under conditions of high work center utilization, the placement of protective capacity immediately before and after the bottleneck with a higher proportion distributed to the upstream work centers may significantly lower bottleneck shiftiness. Several future research needs are discussed.     

A framework for evaluating remote diagnostics investment decisions for semiconductor equipment suppliers

With advances in information technology, service activities for expensive equipment used in semiconductor manufacturing can be performed from a remote location. This capability is called remote diagnostics (RD). Currently, there are intense development efforts in the semiconductor industry for implementing RD in wafer fabrication facilities to reduce maintenance and capital costs and improve productivity. In this paper, we develop a queueing-location model to analyze the capacity and location problem of after sales service providers, considering the effects of RD technology. Our model optimizes the location, capacity and the type of service centers while taking congestion effects into consideration. We solve this model using a simulation optimization approach in which we use a genetic algorithm to search the solution space. We demonstrate how our methodology can be used in strategic investment planning regarding the adoption of RD technology and service center siting through a realistic case study.     

Managing production with flexible capacity deployment for serial multi-stage manufacturing systems

This paper presents a model for serial multi-stage manufacturing systems facing variability from two sources. One source is demand uncertainty; the other is manufacturing uncertainty associated with all manufacturing stages. A production control policy based on the planned lead time and the manufacturing capacity requirement is developed. It is shown that this production control policy has the effect of reducing the variance of production output for all manufacturing stages. Some specific analyses are provided to illustrate the production control policy developed. The model developed provides a vehicle for examining the interrelationships among the production output, the planned lead time and the actual manufacturing flow time. The risk-pooling value over both demand randomness and manufacturing uncertainty, which is achieved through consolidating some manufacturing capacity and deploying flexible capacity among the manufacturing stages, is analyzed. This risk-pooling value can be realized in the form of either reduced manufacturing flow time or increased effective capacity to meet more demand. It is shown that the risk-pooling value increases as the planned lead time decreases.     

An Investigation of Visual Interactive Simulation Methods Using the Job-Shop Scheduling Problem

This paper describes the use of the job-shop scheduling problem in order to investigate the potential of visual interactive simulation methods. Batch simulation methods are compared with visual interactive simulation methods for the job-shop problem. The paper shows that improved solutions can be obtained by having a visual, dynamic representation of a job-shop problem.     

Selecting optimum maintenance strategy by fuzzy interactive linear assignment method

In the current competitive environment managers of manufacturing and service organizations try to make their organizations competitive by providing timely delivery of high quality products. Maintenance, as a system, plays a key role in reducing cost, minimizing equipment downtime, improving quality, increasing productivity and providing reliable equipment and as a result achieving organizational goals and objectives. This paper presents a new approach for selecting optimum maintenance strategy using qualitative and quantitative data through interaction with the maintenance experts. This approach has been based on linear assignment method (LAM) with some modifications to develop interactive fuzzy linear assignment method (IFLAM).     

Parallel simulation by multi-instruction,longest-path algorithms

This paper presents several basic algorithms for the parallel simulation of G/G/1 queueing systems and certain networks of such systems. The coverage includes systems subject to manufacturing or communication blocking, or to loss of customer due to capacity constraints. The key idea is that the customer departure times are represented by longest-path distance in directed graphs instead of by the usual recursive equations. This representation leads to scalable algorithms with a high degree of parallelism that can be implemented on either MIMD or SIMD parallel computers. This revised version was published online in June 2006 with corrections to the Cover Date.     

From competitive to collaborative supply networks: A simulation study

In a scenario where a vendor books its manufacturing capacity options to multiple retailers it is not unlikely that the vendor runs out of capacity and then it cannot serve more orders until future periods of time. This paper suggests that, once the vendor becomes a bottleneck for the network, it is possible to apply negotiation policies between the different retailers to allow re-allocation of options and then overcome this loose/loose situation. Two simple policies to carry out bookings through negotiation practices, allowing partial bookings and not allowing them, are presented in this study. The effectiveness of this approach is tested with a series of simulation experiments whose main results demonstrate that application of negotiation practices within the network when the vendor has not more available capacity to be booked leads to improve the service level, the overall profit and to diminish the sales opportunity cost.     

Quantile regression metamodeling: Toward improved responsiveness in the high-tech electronics manufacturing industry

Both technology and market demands within the high-tech electronics manufacturing industry change rapidly. Accurate and efficient estimation of cycle-time (CT) distribution remains a critical driver of on-time delivery and associated customer satisfaction metrics in these complex manufacturing systems. Simulation models are often used to emulate these systems in order to estimate parameters of the CT distribution. However, execution time of such simulation models can be excessively long limiting the number of simulation runs that can be executed for quantifying the impact of potential future operational changes. One solution is the use of simulation metamodeling which is to build a closed-form mathematical expression to approximate the input–output relationship implied by the simulation model based on simulation experiments run at selected design points in advance. Metamodels can be easily evaluated in a spreadsheet environment “on demand” to answer what-if questions without needing to run lengthy simulations. The majority of previous simulation metamodeling approaches have focused on estimating mean CT as a function of a single input variable (i.e., throughput). In this paper, we demonstrate the feasibility of a quantile regression based metamodeling approach. This method allows estimation of CT quantiles as a function of multiple input variables (e.g., throughput, product mix, and various distributional parameters of time-between-failures, repair time, setup time, loading and unloading times). Empirical results are provided to demonstrate the efficacy of the approach in a realistic simulation model representative of a semiconductor manufacturing system.     

Aggregation and disaggregation in hierarchical production planning

This paper reports on a simulation study of hierarchical planning procedures, which can support a material requirements planning system. Data for this study have been obtained from a Swedish manufacturing company. The three final products considered in the simulations represent a major part of this company.An aggregate plan in terms of product groups and machine groups is derived with the aid of an aggregate model. This plan is then disaggregated by changing order release times obtained from material requirements planning, and by distributing extra capacity among individual machines.The results indicate that our methods in general perform significantly better than a comparable reference case without the supporting hierarchical planning process. In our simulation experiments we evaluate different design features, like disaggregation procedures and methods for aggregating items and machines.     

Control Strategy for Dispatching Multi-load Automated Guided Vehicles in a Deadlock-Free Environment

The issue of avoiding deadlocks in unmanned automated manufacturing systems with automated guided vehicle systems is addressed in this paper. In the automated guided vehicle systems, multi-load vehicles are used. A simple and easily adoptable deadlock-free real-time vehicle control strategy is developed for this type of vehicle, by using an intelligent rule-based method. The proposed strategy uses the global information and current states of the system to control the resource allocation. Based on the proposed strategy, the system resource can be appropriately allocated and utilized efficiently. A hypothetical system is built to investigate the performance of the proposed vehicle control strategy and to discuss the interactions between the fleet size, queuing capacity, and vehicle loading capacity by computer simulation tool.