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

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

A catalog of stream processing optimizations

Cataloged from PDF version of article.Various research communities have independently arrived at stream processing as a programming model for efficient and parallel computing. These communities include digital signal processing, databases, operating systems, and complex event processing. Since each community faces applications with challenging performance requirements, each of them has developed some of the same optimizations, but often with conflicting terminology and unstated assumptions. This article presents a survey of optimizations for stream processing. It is aimed both at users who need to understand and guide the system's optimizer and at implementers who need to make engineering tradeoffs. To consolidate terminology, this article is organized as a catalog, in a style similar to catalogs of design patterns or refactorings. To make assumptions explicit and help understand tradeoffs, each optimization is presented with its safety constraints (when does it preserve correctness?) and a profitability experiment (when does it improve performance?). We hope that this survey will help future streaming system builders to stand on the shoulders of giants from not just their own community. © 2014 ACM

The hArtes Tool Chain

This chapter describes the different design steps needed to go from legacy code to a transformed application that can be efficiently mapped on the hArtes platform

Matlab

This book is a collection of 19 excellent works presenting different applications of several MATLAB tools that can be used for educational, scientific and engineering purposes. Chapters include tips and tricks for programming and developing Graphical User Interfaces (GUIs), power system analysis, control systems design, system modelling and simulations, parallel processing, optimization, signal and image processing, finite different solutions, geosciences and portfolio insurance. Thus, readers from a range of professional fields will benefit from its content

Control of Energy Storage

Energy storage can provide numerous beneficial services and cost savings within the electricity grid, especially when facing future challenges like renewable and electric vehicle (EV) integration. Public bodies, private companies and individuals are deploying storage facilities for several purposes, including arbitrage, grid support, renewable generation, and demand-side management. Storage deployment can therefore yield benefits like reduced frequency fluctuation, better asset utilisation and more predictable power profiles. Such uses of energy storage can reduce the cost of energy, reduce the strain on the grid, reduce the environmental impact of energy use, and prepare the network for future challenges. This Special Issue of Energies explore the latest developments in the control of energy storage in support of the wider energy network, and focus on the control of storage rather than the storage technology itself

Future value based single assignment program representations and optimizations

An optimizing compiler internal representation fundamentally affects the clarity, efficiency and feasibility of optimization algorithms employed by the compiler. Static Single Assignment (SSA) as a state-of-the-art program representation has great advantages though still can be improved. This dissertation explores the domain of single assignment beyond SSA, and presents two novel program representations: Future Gated Single Assignment (FGSA) and Recursive Future Predicated Form (RFPF). Both FGSA and RFPF embed control flow and data flow information, enabling efficient traversal program information and thus leading to better and simpler optimizations. We introduce future value concept, the designing base of both FGSA and RFPF, which permits a consumer instruction to be encountered before the producer of its source operand(s) in a control flow setting. We show that FGSA is efficiently computable by using a series T1/T2/TR transformation, yielding an expected linear time algorithm for combining together the construction of the pruned single assignment form and live analysis for both reducible and irreducible graphs. As a result, the approach results in an average reduction of 7.7%, with a maximum of 67% in the number of gating functions compared to the pruned SSA form on the SPEC2000 benchmark suite. We present a solid and near optimal framework to perform inverse transformation from single assignment programs. We demonstrate the importance of unrestricted code motion and present RFPF. We develop algorithms which enable instruction movement in acyclic, as well as cyclic regions, and show the ease to perform optimizations such as Partial Redundancy Elimination on RFPF

The effect of overloading on reliability of wheel loader structural components

This research attempts to provide a fundamental understanding into the relationship between the productivity of material handling equipment, specifically wheel loaders, and their ability to operate reliably when subjected to high overload conditions. The overall aim is to determine the effect of overloading the bucket on wheel loader reliability. The specific objectives of the research are to: 1) evaluate the effect of overloading the bucket on wheel loader productivity; 2) examine the effect of overloading the bucket on hydraulic pressures in the hoist cylinders (used as a proxy for forces on a wheel loader); and 3) investigate the effect of overloading the bucket on the reliability of structural components of a wheel loader. To achieve these objectives, the research used data from on-board equipment monitors from the global fleet of ultra-class wheel loaders for a specific original equipment manufacturer to test the various research hypotheses. The data included production data, failure and repair data, and hydraulic cylinder pressures, which were used as a proxy for stresses on structural components. ANOVA and Pearson and Spearman correlations tests were performed on data samples to test the hypotheses. Duty-cycle relationships were established using linear life stress relationships ratios for the wheel loaders structural components. The research showed that, while higher bucket loads increase productivity, there is evidence that they slow down the loading cycle, may be detrimental to productivity. The hoist cylinder pressure increased with increasing payload weight. The reliability of the structural components was similar in both the standard and duty-cycle cases; although, the accuracy of the reliability models increased when the models accounted for duty-cycles --Abstract, page iii

Programmation linéaire en nombres entiers pour l'ordonnancement cyclique sous contraintes de ressources

Un problème d'ordonnancement cyclique consiste à ordonner dans le temps l'exécution répétitive d'un ensemble d'opérations liées par des contraintes de précédence, en utilisant un nombre limité de ressources. Ces problèmes ont des applications immédiates dans les systèmes de production ou en informatique parallèle. Particulièrement, ils permettent de modéliser l'ensemble des contraintes de précédence et de ressource à prendre en compte pour l'ordonnancement d'instructions dans les processeurs de type VLIW (Very Long Instruction Word). Dans ce cas, une opération représente une instance d'une instruction dans un programme. L'ordonnancement d'instructions de boucles internes est connu sous le nom de pipeline logiciel. Le pipeline logiciel désigne une méthode efficace pour l'optimisation de boucles qui permet la réalisation en parallèle des opérations des différentes itérations de la boucle. Dans cette thèse, nous nous intéressons principalement au problème d'ordonnancement périodique qui est un cas particulier de l'ordonnancement cyclique et qui est également la base du pipeline logiciel. Le terme ordonnancement modulo désigne un ordonnancement périodique tel que l'allocation de ressources pour une opération donnée n'est pas modifiée d'une itération sur l'autre. Pour résoudre le problème, nous nous intéressons aux formulations de programmation linéaire en nombres entiers, et notamment à la résolution du problème par des techniques de séparation, évaluation, génération de colonnes, relaxation lagrangienne et des méthodes hybrides. En particulier, nous proposons des nouvelles formulations basées sur des variables binaires représentant l'exécution d'ensembles d'instructions en parallèle. Enfin, les méthodes développées ont été validées sur des jeux d'instances industrielles pour des processeurs de type VLIW.The resource-constrained modulo scheduling problem (RCMSP) is a general periodic cyclic scheduling problem, abstracted from the problem solved by compilers when optimizing inner loops at instruction level for very long instruction word parallel processors. Since solving the instruction scheduling problem at compilation phase in less time critical than for real time scheduling, integer linear programming (ILP) is a relevant technique for the RCMSP. In this work, we are interested in the methods based on the integer linear programming for the RCMSP. At first, we present a study of the two classic integer linear formulation for the RCMSP. A theoretical evidence of the equivalence between the classic formulations is shown in terms of linear programming (LP) relaxation. Secondly, based on the ILP formulations for the RCMSP, stronger formulations for the RCMSP derived from Dantzig-Wolfe decomposition are presented. In these formulations, the number of variables can be huge, for this reason, we proposed a column generation scheme to solve their LP relaxations. We propose also the heuristics methods based on the Lagragian relaxation and decomposed software pipelining. The heuristic methods search the transformation of the classic integer linear programming for the RCMSP for the performance improvement in the time for the search of solutions. All formulations are compared experimentally on problem instances generated from real data issued from the STMicroelectronics ST200 VLIW processor family

Third CLIPS Conference Proceedings, volume 1

Expert systems are computed programs which emulate human expertise in well defined problem domains. The potential payoff from expert systems is high: valuable expertise can be captured and preserved, repetitive and/or mundane tasks requiring human expertise can be automated, and uniformity can be applied in decision making processes. The C Language Integrated Production Systems (CLIPS) is an expert system building tool, developed at the Johnson Space Center, which provides a complete environment for the development and delivery of rule and/or object based expert systems. CLIPS was specifically designed to provide a low cost option for developing and deploying expert system applications across a wide range of hardware platforms. The development of CLIPS has helped to improve the ability to deliver expert systems technology throughout the public and private sectors for a wide range of applications and diverse computing environments

Novel approaches to cyclic job-shop problems with transportation

Scheduling problems can be found in almost any field of application in the real world. These problems may not only have different characteristics but they also imply more or less complex requirements. One specific class within this domain is the cyclic job-shop problem. It occurs in various areas reaching from industrial production planning down to the systems architecture of computers. With manufacturers in particular, one can find increasing demand for effective solution methods in order to tackle these scheduling problems efficiently. This thesis will deal with the Cyclic Job-Shop Problem with Blocking and Transportation. It arises in modern manufacturing companies, where the products move automatically between the different workstations, for instance. The problem itself is not new to the research community, but hardly any work has been done in solving it. Within this thesis we will try to close this gap and present some first approaches, discussing the structure of the problem and how it can be solved. As a result, we will provide three different solution methods, including an integer programming formulation, which is solved with a commercial solver, a branch and bound algorithm and a tabu search heuristic. All algorithms are tested on a range of data sets and compared with each other. Additionally, we have worked on a polynomial solvable subproblem, which has gained more interest in the literature. As a result, a new polynomial algorithm, that outperforms the existing ones in theory as well as in empirical tests (except for some special cases) is presented. This thesis concludes with a discussion about ideas of how to improve the presented methods and some other extensions to the investigated problem