The role of learning on industrial simulation design and analysis

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

Experimental analysis of computer system dependability

This paper reviews an area which has evolved over the past 15 years: experimental analysis of computer system dependability. Methodologies and advances are discussed for three basic approaches used in the area: simulated fault injection, physical fault injection, and measurement-based analysis. The three approaches are suited, respectively, to dependability evaluation in the three phases of a system's life: design phase, prototype phase, and operational phase. Before the discussion of these phases, several statistical techniques used in the area are introduced. For each phase, a classification of research methods or study topics is outlined, followed by discussion of these methods or topics as well as representative studies. The statistical techniques introduced include the estimation of parameters and confidence intervals, probability distribution characterization, and several multivariate analysis methods. Importance sampling, a statistical technique used to accelerate Monte Carlo simulation, is also introduced. The discussion of simulated fault injection covers electrical-level, logic-level, and function-level fault injection methods as well as representative simulation environments such as FOCUS and DEPEND. The discussion of physical fault injection covers hardware, software, and radiation fault injection methods as well as several software and hybrid tools including FIAT, FERARI, HYBRID, and FINE. The discussion of measurement-based analysis covers measurement and data processing techniques, basic error characterization, dependency analysis, Markov reward modeling, software-dependability, and fault diagnosis. The discussion involves several important issues studies in the area, including fault models, fast simulation techniques, workload/failure dependency, correlated failures, and software fault tolerance

Manufacturing flow line systems: a review of models and analytical results

The most important models and results of the manufacturing flow line literature are described. These include the major classes of models (asynchronous, synchronous, and continuous); the major features (blocking, processing times, failures and repairs); the major properties (conservation of flow, flow rate-idle time, reversibility, and others); and the relationships among different models. Exact and approximate methods for obtaining quantitative measures of performance are also reviewed. The exact methods are appropriate for small systems. The approximate methods, which are the only means available for large systems, are generally based on decomposition, and make use of the exact methods for small systems. Extensions are briefly discussed. Directions for future research are suggested.National Science Foundation (U.S.) (Grant DDM-8914277

Performance evaluation of flexible manufacturing systems under uncertain and dynamic situations

The present era demands the efficient modelling of any manufacturing system to enable it to cope with unforeseen situations on the shop floor. One of the complex issues affecting the performance of manufacturing systems is the scheduling of part types. In this paper, the authors have attempted to overcome the impact of uncertainties such as machine breakdowns, deadlocks, etc., by inserting slack that can absorb these disruptions without affecting the other scheduled activities. The impact of the flexibilities in this scenario is also investigated. The objective functions have been formulated in such a manner that a better trade-off between the uncertainties and flexibilities can be established. Consideration of automated guided vehicles (AGVs) in this scenario helps in the loading or unloading of part types in a better manner. In the recent past, a comprehensive literature survey revealed the supremacy of random search algorithms in evaluating the performance of these types of dynamic manufacturing system. The authors have used a metaheuristic known as the quick convergence simulated annealing (QCSA) algorithm, and employed it to resolve the dynamic manufacturing scenario. The metaheuristic encompasses a Cauchy distribution function as a probability function that helps in escaping the local minima in a better manner. Various machine breakdown scenarios are generated. A ‘heuristic gap’ is measured, and it indicates the effectiveness of the performance of the proposed methodology with the varying problem complexities. Statistical validation is also carried out, which helps in authenticating the effectiveness of the proposed approach. The efficacy of the proposed approach is also compared with deterministic priority rules

An analysis of random mechanical failures of bucket wheel excavator

In this article random mechanical failures of bucket wheel excavator at open cast mine "Tamnava Zapad" are analysed. Random mechanical failures of mining equipment may represent an important factor in coal production because these types of failures occur unpredictably. Some of the reasons for the occurrence of such failures are unde-tectable defects, unexplainable causes, and unavoidable failures. In addition, here we have failure of equipment that has a large investment and productivity value. Statistical regularity of the component failure distribution of this system is analysed based on dispatcher's reports about EBS system failures in the period 2003-2011. The proposed distribution is analysed by theoretically, using suitable tests. By using statistical distribution we get the expected uptime of the bucket wheel excavator, for each year, which represents an important factor in maintenance programs and periodic inspections/repairs on bucket wheel excavator and mining components, in general

An analysis of random mechanical failures of bucket wheel excavator

In this article random mechanical failures of bucket wheel excavator at open cast mine "Tamnava Zapad" are analysed. Random mechanical failures of mining equipment may represent an important factor in coal production because these types of failures occur unpredictably. Some of the reasons for the occurrence of such failures are unde-tectable defects, unexplainable causes, and unavoidable failures. In addition, here we have failure of equipment that has a large investment and productivity value. Statistical regularity of the component failure distribution of this system is analysed based on dispatcher's reports about EBS system failures in the period 2003-2011. The proposed distribution is analysed by theoretically, using suitable tests. By using statistical distribution we get the expected uptime of the bucket wheel excavator, for each year, which represents an important factor in maintenance programs and periodic inspections/repairs on bucket wheel excavator and mining components, in general

Looking Into the Black Box: A Survey of the Matching Function

We survey the microfoundations, empirical evidence and estimation issues underlying the aggregate matching function. Several microeconomic matching mechanisms have been suggested in the literature with some successes but none is generally accepted as superior to all others. Instead, an aggregate matching function with hires as a function of vacancies and unemployment has been successfully estimated for several countries. The Cobb-Douglas restrictions with constant returns to scale perform well. Recent work has utilized disaggregated data to go beyond aggregate estimates, with many refinements and suggestions for future research.Matching function, search, mismatch, Beveridge curve, co-ordination failure, stock-flow matching, ranking, on-the-job search, space aggregation, time aggregation