41,260 research outputs found

    APPROXIMATE ANALYSIS OF RE-ENTRANT LINES WITH BERNOULLI RELIABILITY MODELS

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    Re-entrant lines are widely used in many manufacturing systems, such as semiconductor, electronics, etc. However, the performance analysis of re-entrant lines is largely unexplored due to its complexity. In this thesis, we present iterative procedures to approximate the production rate of re-entrant lines with Bernoulli reliability of machines. The convergence of the algorithms, uniqueness of the solution, and structural properties, have been proved analytically. The accuracy of the procedures is investigated numerically. It is shown that the approaches developed can either provide a lower bound or a closed estimate of the system production rate. Finally, a case study of automotive ignition component line with re-entrant washing operations is introduced to illustrate the applicability of the method. The results of this study suggest a possible route for modeling and analysis of re-entrant systems

    Multivariable stability analysis of position-controlled payloads to support shrink in semiconductor manufacturing

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    This paper addresses the challenge of ever-smaller structures in the semiconductor industry and the resulting requirements for high-performance mechatronic systems, especially wafer scanners, in lithography processes in the context of mechatronic system design and analysis. As a result, the development of sophisticated methods for modeling, control, and analysis of control systems has become necessary. To meet this need, advanced analysis methods of multivariable control systems are investigated, in particular the combination of classical stability analysis methods like the Nyquist criteria and use of Individual Channel Analysis and Design (ICAD) methods. For this purpose, the requirements for the analysis of multivariable control systems are summarized and put in the context of classical methods of system analysis, for example, the use of Nyquist methods to evaluate the stability of the control loop. Subsequently, the paper provides a rationale for why the use of Single-Input Single-Output (SISO) methods to assess stability and robustness is not sufficient and how these can be extended to Multiple-Input Multiple Output (MIMO) methods to meet the requirements. A set of tailored Nyquist-like MIMO analysis methods are theoretically derived, including the ICAD method and classical Nyquist stability analysis and its use in the analysis of multivariable control system is explained. A coupling ratio parameter, quantifying the coupling of multivariable systems, is derived from the extended ICAD method. The iterative design process is explained, which allows conclusions to be drawn about individual system parameters and how to optimize them to achieve high performance. To compare the methods, a model of a mechanical payload with variable eigenfrequencies is derived. Subsequently, the suitability of the respective method for multivariable stability analysis is tested in different system configurations. In conclusion, this paper provides insight into the analysis of stability and robustness of multivariable control systems and presents the challenges and opportunities of using these advanced methods to design high-performance mechatronics in the context of increasing requirements due to the shrink in semiconductor manufacturing. This provides a valuable contribution to the design of high-performance mechatronic systems

    Semiconductor manufacturing simulation design and analysis with limited data

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    This paper discusses simulation design and analysis for Silicon Carbide (SiC) manufacturing operations management at New York Power Electronics Manufacturing Consortium (PEMC) facility. Prior work has addressed the development of manufacturing system simulation as the decision support to solve the strategic equipment portfolio selection problem for the SiC fab design [1]. As we move into the phase of collecting data from the equipment purchased for the PEMC facility, we discuss how to redesign our manufacturing simulations and analyze their outputs to overcome the challenges that naturally arise in the presence of limited fab data. We conclude with insights on how an approach aimed to reflect learning from data can enable our discrete-event stochastic simulation to accurately estimate the performance measures for SiC manufacturing at the PEMC facility

    Limits on Fundamental Limits to Computation

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    An indispensable part of our lives, computing has also become essential to industries and governments. Steady improvements in computer hardware have been supported by periodic doubling of transistor densities in integrated circuits over the last fifty years. Such Moore scaling now requires increasingly heroic efforts, stimulating research in alternative hardware and stirring controversy. To help evaluate emerging technologies and enrich our understanding of integrated-circuit scaling, we review fundamental limits to computation: in manufacturing, energy, physical space, design and verification effort, and algorithms. To outline what is achievable in principle and in practice, we recall how some limits were circumvented, compare loose and tight limits. We also point out that engineering difficulties encountered by emerging technologies may indicate yet-unknown limits.Comment: 15 pages, 4 figures, 1 tabl

    The role of learning on industrial simulation design and analysis

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    The capability of modeling real-world system operations has turned simulation into an indispensable problemsolving methodology for business system design and analysis. Today, simulation supports decisions ranging from sourcing to operations to finance, starting at the strategic level and proceeding towards tactical and operational levels of decision-making. In such a dynamic setting, the practice of simulation goes beyond being a static problem-solving exercise and requires integration with learning. This article discusses the role of learning in simulation design and analysis motivated by the needs of industrial problems and describes how selected tools of statistical learning can be utilized for this purpose

    Simulation Based Study of Safety Stocks under Short-Term Demand Volatility in Integrated Device Manufacturing.

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    © IEOM Society InternationalA problem faced by integrated device manufacturers (IDMs) relates to fluctuating demand and can be reflected in long-term demand, middle-term demand, and short-term demand fluctuations. This paper explores safety stock under short term demand fluctuations in integrated device manufacturing. The manufacturing flow of integrated circuits is conceptualized into front end and back end operations with a die bank in between. Using a model of the back-end operations of integrated circuit manufacturing, simulation experiments were conducted based on three scenarios namely a production environment of low demand volatility and high capacity reliability (Scenario A), an environment with lower capacity reliability than scenario A (Scenario B), and an environment of high demand volatility and low capacity reliability (Scenario C). Results show trade-off relation between inventory levels and delivery performance with varied degree of severity between the different scenarios studied. Generally, higher safety stock levels are required to achieve competitive delivery performance as uncertainty in demand increases and manufacturing capability reliability decreases. Back-end cycle time are also found to have detrimental impact on delivery performance as the cycle time increases. It is suggested that success of finished goods safety stock policy relies significantly on having appropriate capacity amongst others to support fluctuations

    Value co-creation characteristics and creativity-oriented customer citizenship behavior

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    For the competitive advantage of service organization, it is important to improve the creative performance of human resources in the organization. For example, when employees perform creatively, in other words, if they generate novel and useful ideas, it will contribute to organizational competiveness. Therefore, there has been an increased focus in identifying its antecedents and consequences. Unfortunately, little is known about the creative performance of customers. According to service-centered dominant logic, customer is the value co-creator, it emphasizes co-opting customer involvement in the value creation process as an additional human resource. In addition, customers can be a valuable resource for service improvement efforts for firms. For instance, companies might benefit greatly from customer feedback and complaints regarding their offerings and can enhance their productivity in terms of quality and quantity. In this paper, the type of novel, creative-oriented customer behaviors highlighted in the preceding paragraph are referred to as creativity-oriented customer citizenship behaviors (CCBs). In the customer value co-creation context, creative-oriented CCBs refer to extra-role efforts by customers with regards the development of ideas about products, practices, services, and procedures that are novel and potentially useful to a firm. According to the intrinsic motivation perspective, the context in which customers create values, influences their intrinsic motivation, which in turn affects creativity-oriented CCBs. The intrinsic motivation perspective suggests that high intrinsic motivation is affected by information from both task characteristics (i.e., autonomy) and social characteristics (e.g., supplier support). Specifically, complex and challenging task characteristics such as high levels of variety, identity, significance, autonomy, and feedback are expected to increase customer intrinsic motivation. Under these conditions, customers should increase the likelihood of creativity-oriented CCBs. Therefore, customers are expected to be most creative when they experience a high level of intrinsic motivation. In contrast, complex and challenging task and social characteristics can have the opposite effect to customers. For example, in a high level of variety task, increased autonomy can lead to increased workload because they must take on related extra responsibilities and accountability. Increased workload, in turn, is expected to lead to decreased likelihood of creativity-oriented CCBs. Therefore, this study attempts to explore the impact of task characteristics and social characteristics on creativity-oriented CCBs. Furthermore, a substantial body of research has examined the possibility that creativity is affected by personal characteristics. As such, in addition to the relevant task and social characteristics, the moderating influence of several trait variables is also considered. This article makes several contributions. First, this study investigates the trade-off effect of the customer value co-creation related task and social characteristics by examining the underlying opposing mechanism of motivation and work overload. Second, this research provides a deeper understanding of contingency factors that systematically strengthen the relationships under consideration. Third, this study may indicate that companies seek to promote the creativity of their industrial customers and should design the tasks and social characteristics of their industrial customers in a way that maximizes their creativity. But, companies should be aware of the negative impact of specific tasks and social characteristics that may minimize the creativity of industrial customers

    Aerospace Manufacturing Industry: A Simulation-Based Decision Support Framework for the Scheduling of Complex Hoist Lines

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    The hoist scheduling problem is a critical issue in the design and control of Automated Manufacturing Systems. To deal with the major complexities appearing in such problem, this work introduces an advanced simulation model to represent the short-term scheduling of complex hoist lines. The aim is to find the best jobs schedule that minimizing the makespan while maximizing throughput with no defective outputs. Several hard constraints are considered in the model: single shared hoist, heterogeneous recipes, eventual recycles flows, and no buffers between workstations. Different heuristic-based strategies are incorporated into the computer model in order to improve the solutions generated over time. The alternative solutions can be quickly evaluated by using a graphical user interface developed together with the simulation model.Fil: Basán, Natalia Paola. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Santa Fe. Instituto de Desarrollo Tecnológico para la Industria Química. Universidad Nacional del Litoral. Instituto de Desarrollo Tecnológico para la Industria Química; ArgentinaFil: Pulido, Raul. Universidad Politécnica de Madrid; EspañaFil: Coccola, Mariana Evangelina. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Santa Fe. Instituto de Desarrollo Tecnológico para la Industria Química. Universidad Nacional del Litoral. Instituto de Desarrollo Tecnológico para la Industria Química; ArgentinaFil: Mendez, Carlos Alberto. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Santa Fe. Instituto de Desarrollo Tecnológico para la Industria Química. Universidad Nacional del Litoral. Instituto de Desarrollo Tecnológico para la Industria Química; Argentin
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