Impact of flexible machines on automated manufacturing systems

Although the problem of scheduling dynamic job shops is well studied, setup and changeover times are often assumed to be negligibly small and therefore ignored. In cases where the product mix changes occur frequently, setup and changeover times are of critical importance. This paper applies some known results from the study of multi-class single-server queues with setup and changeover times to develop an approximation for evaluating the performance of job shops. It is found that the product mix, setup and changeover times, and scheduling rules affect the performance significantly, in particular at high levels of machine utilisation. This approach could be used to determine the required level of flexibility of machines and to choose an appropriate scheduling policy such that production rates remain within acceptable limits for foreseeable changes in the product mix.     

A closed queuing maintenance network for automated manufacturing systems

This paper models an unreliable automated manufacturing system (AMS) by a closed queuing network. The AMS consists of a multi-stage network of automated work stations linked by a computer. A closed queuing algorithm is applied to determine the system availability under steady state for the AMS. This algorithm is then integrated into a cost optimization model. By applying the revised genetic algorithm, the optimal (or near-optimal) number of standby units and repair rates for the repair stations are derived by minimizing the total cost. The model is verified by the intuitive results from the sensitivity analysis. A numerical example is used to compare the revised genetic algorithm and the conventional genetic algorithm. The results show that the proposed revised algorithm leads to significant improvement in execution time and lower average total cost.     

Optimized material requirements planning for semiconductor manufacturing

This paper describes a custom operational research algorithm, which is run nightly by IBM to create a material requirements plan for its semiconductor fabrication facility in Vermont, USA. To model alternative manufacturing processes and part substitutions, this application interweaves linear programming and heuristic methods to reap the benefits of each decision technology. At each level of the bills of materials supply chain with complex decision choices to be made, parallel linear programmes are invoked and their results are fed into a material requirements planning (MRP) heuristic, which processes parts through multiple iterations. The results from processing one level of the bills of materials supply chain are exploded to create demand for the next level and the interweaving of the two decision technologies continues. The algorithm creates recommended manufacturing releases and work-in-process priorities. These outputs point out opportunities for improvement in order to satisfy all demands on time. The output can be interpreted with well-known MRP assumptions.     

Contracting over multiple parameters: Capacity allocation in semiconductor manufacturing

This paper is a generalization of Mallik and Harker [Mallik, S., Harker, P.T., 2004. Coordinating supply chains with competition: Capacity allocation in semiconductor manufacturing. European Journal of Operational Research 159, 330–347] that presented an integrated model of incentive problems arising in forecasting and capacity allocation. In that model, multiple product managers and multiple manufacturing managers forecast the means of their respective demand and capacity distributions, and a central coordinator allocates capacities based on these forecasts. A mechanism that elicits truthful information from the managers was the main contribution of that paper. The objective of this paper is to generalize our previous results to multiple statistics reporting. This work assumes that the central coordinator can ask the managers to report multiple statistics (mean and variance, for example) about their respective distributions. We propose a game theoretic model and design a mechanism (a bonus scheme and an allocation rule) that elicits truthful reporting of all statistics by all managers. It turns out that the structure of the optimal bonus schemes are rather simple with easily calculable parameters. We also show that a large class of allocation rules are manipulable. A bonus is often required for elicitation of truthful information. We compare our results of multiple statistics reporting with those from Mallik and Harker (2004). We also characterize under what conditions the reporting of the extra information is of limited use.     

Minimizing makespan on a single burn-in oven in semiconductor manufacturing

This paper considers a scheduling problem for a single burn-in oven in semiconductor manufacturing industry where the oven is a batch processing machine and each batch processing time is represented by the largest processing time among those of all the jobs contained in the batch. The objective measure of the problem is the maximum completion time (makespan) of all jobs. This paper investigates a static case in which all jobs are available to process at time zero, and also analyzes a dynamic case with different job-release times, for which a branch-and-bound algorithm and several heuristics are exploited. The worst case error performance ratios of the heuristics are also derived.     

Batching in single operation manufacturing systems

We introduce a new decision problem important to the efficient operation of resources in manufacturing systems. This problem of ‘batching’ is considered for single machine activities. It is shown that even for these simple models, lot splitting may occur and that these batching decisions may have a dramatic impact on the manufacturing lead time of items to be processed.     

Inner and outer loop optimization in semiconductor manufacturing supply chain management

Supply chain management (SCM) in semiconductor manufacturing differs from many other SCM applications in that it has to simultaneously consider both long and short time scale stochasticity and nonlinearity. We present a two-level hierarchical structure for SCM motivated by these considerations. A linear programming (LP)-based strategic planning module forms the outer loop which makes long timescale decisions on the starts of factories. A model predictive control (MPC) based tactical execution module forms the inner loop which generates short timescale decisions on the starts of factories by considering the stochasticity and nonlinearity on both supply and demand sides. Two representative case studies are examined under diverse realistic conditions with this integrated framework. It is demonstrated that given conditions of stochasticity, nonlinearity, and forecast error this hierarchical decision structure can be tuned to manage representative semiconductor manufacturing supply chains in a manner appealing to operations. This work was supported by grants from the Intel Research Council and the National Science Foundation (CMMI-0432429).     

Sequencing jobs for an automated manufacturing module with buffer

This article deals with the real-time scheduling of jobs for an automated manufacturing module offering a variety of operations with negligible setup times. Since the jobs are brought to the system by a paced line at a fixed rate, each job is expected to be processed within a fixed cycle time. Hence, a group of jobs with longer processing-time may cause immediate accumulation of jobs in the limited input buffer. Consequently, an arriving job may be blocked from entering until the job in the station is completed. A Dynamic Program is implemented to schedule the jobs with the minimum total blocking time. Depending on the data, this implementation may become computationaly intractable, and thereby, a heuristic is developed to produce good solutions in polynomial time. The worst case error bounds are established for the heuristic solutions. An extensive experimentation shows that the heuristic yields close to optimal solutions effectively.     

Some statistical challenges in automated driving systems

Automated driving systems are rapidly developing. However, numerous open problems remain to be resolved to ensure this technology progresses before its widespread adoption. A large subset of these problems are, or can be framed as, statistical decision problems. Therefore, we present herein several important statistical challenges that emerge when designing and operating automated driving systems. In particular, we focus on those that relate to request-to-intervene decisions, ethical decision support, operations in heterogeneous traffic, and algorithmic robustification. For each of these problems, earlier solution approaches are reviewed and alternative solutions are provided with accompanying empirical testing. We also highlight open avenues of inquiry for which applied statistical investigation can help ensure the maturation of automated driving systems. In so doing, we showcase the relevance of statistical research and practice within the context of this revolutionary technology.     

Minimax production planning in failure-prone manufacturing systems

In this paper, we consider a minimax production planning model of a flexible manufacturing system with machines that are subject to random breakdown and repair. The objective is to choose the rate of production that minimizes the related minimax cost of production and inventory/shortage. The value function is shown to be the unique viscosity solution to the associated Hamilton-Jacobi-Isaacs equation. Under certain conditions, it is shown that the value function is continuously differentiable. A verification theorem is given to provide a sufficient condition for optimal control. Finally, two examples are solved explicitly.This research was supported by the Natural Sciences and Engineering Research Council of Canada under Grants OGP0036444 and A4169.     

Optimal yield improvement in multi-stage manufacturing systems

Multi-stage manufacturing systems producing some non-conforming items still present economic operational problems. A decomposition approach is presented to model multi-stage manufacturing systems with inspection stations. The concept of process improvement as developed is expressed in terms of a step-wise yield improvement path, along which the most profitable improvement stages are identified. It is shown that the model selects an ever increasing set of stations to improve, once the profitability of the best station-candidates reaches a level similar to that of some other station-candidates. The approach also extends the concept of an event (naturally connected to a time frame) by relating it to a dynamic profitability frame. From an operational perspective the findings suggest that a quality improvement project, initially undertaken by a cross-functional team at a multi-stage level, may be continued through concurrent projects, focusing on improving the quality of specific manufacturing stages. The research results may be directly extended to include integrated economic improvement-inspection decisions.     

Expert systems for planning and scheduling manufacturing systems

In this paper, research and applications of expert systems in production planning and scheduling are reviewed. Components of expert systems are briefly discussed. Relationship between expert system and operations research approaches are presented. Integration of operations research and expert system techniques is explored.     

Auxiliary tool allocation in flexible manufacturing systems

This paper analyses a new approach to the machine loading problem arising in flexible manufacturing systems (FMSs). This approach allows the operations to be assigned to machines assuming that machines have access to all the tools required for their operations. This exploits the flexibility of the FMS completely. Next an allocation of tools to machines is determined which satisfies the tool requirements for each machine and minimizes the total number of tools. Thus this approach minimizes the unnecessary tool duplications in the system and maximizes the tool utilization. The problem is modeled as an integer linear program (ILP). We notice that the main problem has a block diagonal structure which is decomposable by relaxing a set of linking constraints. Each separated sub-problem represents a problem of allocation of a single type of tools. We develop a branch-and-bound based exact solution procedure and three heuristic procedures to solve the sub-problems. Our lower bounding approach uses Lanrangean relaxation. The solutions to the Lagrangean relaxation are further used to determine the branching sequences and to develop heuristic approaches. Since finding even a feasible solution to the main problem is NP-hard, we develop only enumerative procedures to solve the main problem. Finally, these solution procedures are tested on randomly generated test problems.     

Asymmetrical response of semiconductor lasers in optical systems

The symmetry of the optical outputs of a semiconductor laser diode having front and rear facets with equal reflectivity is destroyed by the injection of a reflected signal, even of weak intensity, from one side: this asymmetry must be taken into account when designing laser packages and integrated circuits. A systematic experimental investigation is presented. Moreover, the behaviour of the system, i.e., the appearance of certain asymmetrical features together with the survival of the symmetry of other features, can be accounted for on the basis of a microscopic model, providing a link between the optical outputs from the two facets.Italtel-Advanced Technology Laboratory Cascino Castelletto, CLTB-20019 Settimo Milanese, Italy. Consorzio Milano Ricerche Via Cicognara, 7-20129 Milano, Italy. Physics Department, University of Milan, Via Celoria, 16-20133 Milano, Italy. Translated from Teoreticheskaya i Matematicheskaya Fizika, Vol. 99, No. 3, pp. 364–369, June, 1994.     

The solution of Lyumkis energy transport model in semiconductor science

The existence and uniqueness of solution to Lyumkis energy transport model is discussed for N+2<p≤q<∞ and 1≤N≤3. Copyright © 2003 John Wiley & Sons, Ltd.     

Internal stress relaxation in polymer systems

In polymer materials phase transition of the system from the liquid to the solid state is associated with internal stresses which act counter to the forces of molecular cohesion and thus reduce the cohesive strength. It has been established that the introduction of elastomers, without seriously affecting the strength properties, substantially reduces the internal stresses in polymer systems and improves the relaxation characteristics.Mekhanika Polimerov, Vol. 2, No. 2, pp. 240–244, 1966     

Dynamic diagnostics of mechanical manufacturing systems

We consider an approach to the computation of the dynamic parameters of a kinematic system based on the Chebyshev approximation of the trajectory of the process. We give recursion relations for estimating the approximation error. Translated fromDinamicheskie Sistemy, Vol. 11, 1992.     

Global and variable cost manufacturing systems

The advent of global manufacturing companies has led to a series of new challenges and problems. One of the more important of these is planning capacity and facilities in the environment of exchange rate uncertainties. While exchange rate uncertainty is a feature of a global environment, the problem formulations actually apply to a wide range of facility and network design problems. This article presents a series of models and results to address these problems.     

Modeling complexity of cellular manufacturing systems

Manufacturing systems are complex because of the many elements and subsystems of a manufacturing operation and their interactions. This study proposes a utility function for complexity and its curve is drawn according to the mutual relationship between the complexity and utility. The underlying trend that the system becomes more and more complex in an ever-changing environment is analyzed in terms of the variation of complexity with time. From the information-theoretical point of view, the models of static entropy and operational entropy of cellular manufacturing systems are developed and the cognizance of the states of manufacturing resources is also illustrated. Finally, an example is used to demonstrate the validity of the proposed methodology.