Showing papers on "Production engineering published in 2013"

Towards adaptable manufacturing systems

Abstract: Life cycles of many products are becoming shorter. In addition, the number of variants of one product is growing. As a fact, volume of one specific product that is being manufactured is decreasing. This leads to more frequent modifications of production lines. To cope with these changes, adaptable manufacturing systems are required. Current manufacturing systems can only be adapted to certain (predefined) situations. Other changes require high effort accompanied with high cost and setup time. In this paper, we focus on adaptivity with respect to IT systems. To increase the adaptability of IT systems for automation, we propose a model-based plug&play approach for integrating new stations. This helps in reducing changeover time and efforts. We propose different models describing stations and their capabilities, the setup of the factory, and the production plans. The system is then monitored automatically and the production is planned using models@run-time. To abstract from different platforms and communication technologies data transfer is handled by a middleware. We evaluate our approach using an industrial production system used for educational purposes.

Measuring complexity in mixed-model assembly workstations

Abstract: In an effort to maintain or increase their market share and at the same time prevent costs from escalating, manufacturing organisations are increasingly using their current manufacturing system to produce custom output. As a consequence, the large number of product variants increases significantly the complexity of manufacturing systems, both for the operators as for the support services. This is especially true in automotive industry, where customisation is increasing at a rapid pace. To counter the ensuing loss of productivity, a more fundamental approach to dealing with this complexity in manufacturing processes is required. In order to investigate the impact of complexity on production performance, one must first delineate the concept and then identify as unambiguously as possible highly complex workstations. This article defines complexity at the workstation level and proposes a complexity measure for mixed-model assembly workstations. Based on data from several leading automotive companies from Belgium and Sweden, some statistical models are proposed to characterise workstations complexity. The models are described and their validity and accuracy are discussed.

Industrial Production Management in Flexible Manufacturing Systems

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Computing in Science and Engineering … in Manufacturing

Abstract: The authors consider the obstacles and discuss the importance of integrating the latest techniques of computational science and engineering into digital manufacturing.

Industrial engineering and management

Abstract: People are the fundamental component of production systems. People provide the creativity and leadership essential to make things happen. Hence, industrial engineering is the most people-oriented discipline within the engineering family. Industrial engineers are trained to think in both broad and specific terms. Practicing industrial engineers understand business parameters as well as physical and social parameters within production systems. This breadth allows industrial engineers to function effectively in a wide spectrum of activities ranging from strategic business planning to detailed task design. The wide-angle vision of industrial engineering provides career flexibility, leading to high-level leadership or specialized technical responsibilities.

Characteristics affecting management of design information in the production system design process

Abstract: Although it has been argued that the design of production systems is crucial, there is a general lack of empirical studies analysing and identifying resources and capabilities required for an effic ...

Evolution of production facilities and its impact on non-functional requirements

Abstract: Due to high acquisition costs, production facilities are to operate for many years or even decades to be profitable. During operation, application and customer requirements change rather frequently. Therefore, a process operator must constantly evolve the control software and the underlying system. This task is restricted by specific constraints in the domain of production systems (e.g. short reaction times, high dependency on physics, etc.) hindering the proper use of formal engineering processes, which results in a lack of explicit documentation. Under such circumstances, it is evident that long-living automation software systems require special strategies to deal with incomplete information. Moreover, due to the complexity of production plants, the interconnection between evolution scenarios and system requirements might be complex. Then, a link between evolution and fulfillment of requirements is to be defined. In an effort to give a structured overview of the resulting difficulties due to improperly performed evolution steps in production facilities, this contribution presents a categorization of evolution scenarios from a practical point of view. In addition, interrelations between physical process measurements and high-level requirements are shown. This paper aims at describing the occurring difficulties within evolving production systems from a practical point of view and establishing a first step towards exploiting process measurements for requirement-aware production systems.

Integrated production planning and control: a multi-objective optimization model

Abstract: Purpose: Production planning and control has crucial impact on the production and business activities of enterprise. Enterprise Resource Planning (ERP) is the most popular resources planning and management system, however there are some shortcomings and deficiencies in the production planning and control because its core component is still the Material Requirements Planning (MRP) . For the defects of ERP system, many local improvement and optimization schemes have been proposed , and improve the feasibility and practicality of the plan in some extent, but study considering the whole planning system optimization in the multiple performance management objectives and achieving better application performance is less. The purpose of this paper is to propose a multi-objective production planning optimization model Based on the point of view of the integration of production planning and control, in order to achieve optimization and control of enterprise manufacturing management. Design/methodology/approach: On the analysis of ERP planning system’s defects and disadvantages, and related research and literature, a multi-objective production planning optimization model is proposed, in addition to net demand and capacity, multiple performance management objectives, such as on-time delivery, production balance, inventory, overtime production, are considered incorporating into the examination scope of the model, so that the manufacturing process could be management and controlled Optimally between multiple objectives. T he validity and practicability of the model will be verified by the instance in the last part of the paper . Findings: The main finding is that production planning management of manufacturing enterprise considers not only the capacity and materials, but also a variety of performance management objectives in the production process , and building a multi-objective optimization model can effectively optimize the management and control of enterprise manufacturing . Practical implications: By setting cost parameters for all kinds of production objectives, mangers can maintain the balances among multiple objectives, and achieve the optimized management and control in the manufacturing process. Originality/value: This paper propose a multi-objective production planning optimization model, which can consider multiple performance management objectives of manufacturing process, and can achieve effective planning and control of production process of enterprise.

Simulation-based planning of maintenance activities in the automotive industry

Abstract: Factories world-wide do not utilize their existing capacity to a satisfactory level. Several studies indicate an average Overall Equipment Efficiency (OEE) of around 55% in manufacturing industry. One major reason is machine downtime leading to substantial system losses culminating in production plans with unsatisfactory robustness. This paper discusses an approach to integrate maintenance strategies into a production planning approach using discrete event simulation. The aim is to investigate how and where in the planning process maintenance strategies can be integrated and how different maintenance strategies influence production performance and the overall robustness of production plans. The approach is exemplified in an automotive case study, integrating strategies for reactive maintenance in a simulation model to support decision making on how repair orders should be prioritized to increase production performance. The results show that introducing priority-based planning of maintenance activities has a potential to increase productivity by approximately 5%.

Production systems engineering: main results and recommendations for management

Abstract: Production Systems Engineering (PSE) is an emerging branch of engineering intended to investigate the fundamental laws that govern production systems and utilise them for analysis, design, and continuous improvement. In this paper, the main results of PSE are overviewed in a format directed at practitioners, and recommendations for management are provided. In addition, PSE Toolbox, which enables applications, is described.

Increasing agility in engineering and runtime of automated manufacturing systems

Abstract: Modifications in product and system requirements as well as adaptations in lot sizes that cannot be foreseen in the initial planning period require rapid changes and, therefore, reconfigurable manufacturing systems. However, traditional automation technologies based on traditional procedural programming languages such as IEC 61131-3 often lack in flexibility. This paper presents two different approaches contributing to this field of research in order to enhance efficiency and flexibility in automation engineering, namely model-based engineering with automated code generation and dynamic orchestration of semantic web services. A combination of both approaches into an integrated concept are discussed, promising significantly increased flexibility and, by that, reconfigurability through ad-hoc code generation from models during deployment time.

Engineering process evaluation: Evaluation of the impact of internationalisation decisions on the efficiency and quality of engineering processes

Abstract: Engineering and installation processes are one cost driver within the life cycle of a technical system. Especially within international projects crossing country borders, the cost distribution and the cost allocation are challenges for the success of the technical system. The engineers usually responsible for the decisions where and by whom an engineering activity has to be executed within the engineering process are usually not able to execute a highly detailed decision and management process as proposed by workflow management systems. Thus, an easier useable approach following the knowledge of these engineers is required. Within this paper such an approach is described combining different modelling and analysis approaches in a new way resulting in an easy way for resource allocation decisions in engineering processes.

Application Integration of Simulation Tools Considering Domain Specific Knowledge

Abstract: Because of the increasing complexity of modern production processes, it is necessary to plan these processes virtually before realizing them in a real environment. On the one hand there are specialized simulation tools simulating a specific production technique with exactness close to the real object of the simulation. On the other hand there are simulations which simulate whole production processes, but often do not achieve prediction accuracy comparable to the specialized tools. The simulation of a production process as a whole achieving the needed accuracy is hard to realize. Incompatible file formats, different semantics used to describe the simulated objects and missing data consistency are the main causes of this integration problem. In this paper, a framework is presented that enables the interconnection of simulation tools of production engineering considering the specific knowledge of a certain domain (e.g. material processing). Therefore, an ontology-based integration approach using domain specific knowledge to identify necessary semantic transformations has been realized. The framework provides generic functionality which, if concretized for a domain, enables the system to integrate any domain specific simulation tool in the process.

A dynamic lot sizing model with carbon emission constraint and multi-mode production: A general property and a polynomially solvable case

Abstract: This paper extends the classical dynamic lot sizing model to the case with carbon emission and multi-mode production. Production activities generate emission and an emission cap is given for each period. The manufacturer is equipped with more than one mode for production. If a mode is less costly for producing one unit of product, it however yields more emission. As a consequence, the maximum production quantity in each period depends on the production mode selected and the emission cap. The model proposed in this paper represents applications in which the production is emission-dependent and constrained by the government-imposed emission regulation. Furthermore, with multi-mode production and emission regulation, emission abatement may be prompted through technological innovation and optimization of production planning. Compared with classical production planning problems, the problem considered here is challenging due to the emission constraint (therefore cumulative production capacity) and the multiple production modes (therefore multiple setup cost structures). In this paper, we present a general property of optimal solutions. Then, we consider a special but practical case involving two production modes. The practicalness stems from the fact that few manufacturers are equipped with more than two technologies, because of the heavy investment required for a new technology. We first prove some properties of optimal solutions. As a consequence, we can focus on solutions with these properties. This enables us to develop a polynomial dynamic programming algorithm to solve the model into optimality.

Kaikaku in production toward creating unique production systems

Abstract: In the business environment characterized by the severe global competition and the fast-paced changes, production functions of manufacturing companies must have a capacity of undertaking not only i ...

Advances in Networked Enterprises: Virtual Organizations, Balanced Automation, and Systems Integration

Abstract: New market trends and the emergence of the so-called Internet-based `new economy' are leading companies to new forms of organization, mostly relying on privileged cooperation links. Nowadays, most manufacturing processes are not carried out by single enterprises. Rather, organizations feel the need to focus on their core competencies and join efforts with others, in order to fulfill the requirements of new products/services demanded by the global market. In a cooperative networked organization, every enterprise is just a node that adds some value to the process; namely, a step in the manufacturing/supply chain. Furthermore, manufacturing companies increasingly encompass what has typically been regarded as the domain of the service sector. They try to establish long-term relationships with their customers, in order to service their needs around a manufactured product. For these reasons, the area of virtual organizations and industrial virtual enterprises is attracting growing interest in terms of research and development, and implementation approaches for new business practices. The main emphasis of this book is on virtual enterprises and other networked organizations, with special focus on: supporting infrastructures and management of distributed business processes, intelligent multi-agent systems, knowledge management, human interfaces, and socio-economical aspects. Also included in the book are related topics on automation, both in manufacturing and transportation. Special attention is assigned to the fact that advances in information technology and new organizational paradigms will be used not only to induce new economic structures, but also to help a sustainable migration of existing systems towards the new economy. When electronic business initiatives attract such widespread attention, it is important to conciliate the `old' and `new' economies under a balanced perspective. Advances in Networked Enterprises is essential reading for researchers and engineering students in production engineering, computer science, electrical engineering, mechanical engineering, industrial sociology, and transportation, as well as for engineers and practitioners in manufacturing and transportation systems organization and planning.

Trends in Precision Manufacturing Based on Intelligent Design and Advanced Metrology

Abstract: ts of extreme importance in present time of worldwide international competition in industry and production engineering to safe time on the one hand and on the other keep an eye on increasingly higher costs of energy and raw materials. Comprehensive knowledge in the areas of market requirements, product and process development and design, intelligent metrology and end of life management are important presuppositions to achieve rapid, agile, waste free and cost-effective production of innovative, customized complex products using next-generation materials as well as to protect the environment by making zero emissions and improve environmental sustainability and reduce the use of energy by using intelligent manufacturing systems.

Real-time data driven monitoring and optimization method for IoT-based sensible production process

Abstract: Typical challenges that manufacturing enterprises are facing now are compounded by lack of timely, accurate, and consistent information of manufacturing resources of shop floor. Recent developments in wireless sensors, communication and information network technologies have created a new era of the internet of things (IoT). In this paper, an overall architecture of the IoT-enabled manufacturing execution system is presented to provide a new paradigm by extending the techniques of IoT to manufacturing field. Under this architecture, the manufacturing things such as operators, machines, pallets, materials etc. can be embedded with sensors to interact with each other. And the real-time data driven monitoring and optimization for IoT-based sensible production process can be achieved to improve shop-floor productivity and quality, reduce the wastes of manufacturing resources, cut the costs in manufacturing logistics, reduce the risk and improve the efficiency in cross-border customs logistics and online supervision, and improve the responsiveness to production changes.

Beyond lean: a framework for fit production systems

Abstract: Western manufacturing companies are facing a challenging environment fraught with strong competition from India, China and other emerging economies. In this context, the effectiveness of the traditional production concepts of leanness and agility is being challenged. Against this background, the need for new manufacturing paradigms is set to provide new knowledge, techniques, and concepts useful for managers to address the difficulties of today’s business environment. This work extends the concept of production management beyond the achievement of efficiency short-term goals into the realms of strategic thinking by creating both the framework and the indices for an integrated production system. This research presents fit manufacturing as a new production model for a holistic manufacturing strategy that links the short-term goals of manufacturing effectiveness and efficiency embodied in lean and agile production strategies with the long-term objective of sustainable enterprise management. The research extends the concept of integration beyond ordinary manufacturing functions into the realms of strategic thinking. The thesis gives an operational definition for the concept of fit manufacturing by describing the structural and operational characteristics of the production philosophy. It proposes the central theme of fit xxiii manufacturing as a manufacturing strategy essential to creating an integrated view of the factory – inside out and vice-versa. The idea of an overall fitness index combining measures of leanness, agility and economic sustainability is put forward and justified and the necessary conditions for fitness are derived. A case study showing an application of these different measures and the overall production fitness index is presented. This research has shown that the fit production model combines the strengths of lean and agile manufacturing, with the long-term sustainability and viability of the enterprise. The model can be used to assess the performance of the production process, to evaluate investment proposals such as adding a new product line or increasing the overall capacity of the factory, and to build the enterprise of the future. Keywords: Fit Manufacturing, Agile, Lean, Economic Sustainability, Integration, Fitness

Integration university–industry: laboratory model for learning lean manufacturing concepts in the academic and industrial environments

Abstract: In the current production scenario, with a globalized economic environment, companies increasingly need to become morecompetitive to face up to the global market. This means production systems are constantly changing in the direction of thereplacement of the low productivity equipment, rearranging the plant layout, the redirection of the transport stream from thesupplier to the end customer and adding new models to plan and control production. All these changes aim to improve productquality and to reduce production lead time by eliminating waste, reducing costs and increasing competitive advantage through theprocess flexibility. For these changes to happen effectively is necessary that the current employees and the future productionengineers are inserted and fit in this new reality. Currently, the Lean Manufacturing concepts are applied in an industrialenvironment to optimize production flow eliminating the waste found in the process. However, there is a challenge to put these concepts effectively in the industrial environment and in the university environment. The traditional learning process based onteacher, classroom, non-integrated theoretical and practical concepts, case studies with static production characteristic (controlledvariable) has been shown to be ineffective in the consolidation of these concepts in a dynamic production environment. Inuniversity, this same model applied in the production engineering course and fragmented into different disciplines makes productionengineers not fully prepared for the challenges of the new industrial environment, requiring an adjustment period. This adaptationwill result in low competitiveness of the company in front of global competitors. Thus, this article aims to present a laboratorymodel for integrated learning of the Lean Manufacturing concepts based in practices able to reproduce the dynamic productionenvironment, thus speeding the process of training employees of the industrial environment and the learning of future productionengineers.

Enhanced energy management in manufacturing through systems integration

Abstract: Energy management concerns a lot of parameters, data and conditions. A holistic view of the plant is necessary to identify the areas with high energy consumption. Hence, energy management has to be integrated in overall production system. Monitoring and control of energy related key performance indicators in different levels is vital and the beginning phase for improving energy efficiency. Therefore, this study aims at developing an approach to improve energy efficiency in manufacturing by facilitating monitoring and control through ICT-supported KPI intelligence serving as a decision support tool to enhance energy management in manufacturing plants. The decision support tool developed based on this approach allows integration of disparate data coming from different multivendor production IT systems in a manufacturing plant by creating a central environment to better monitor and control energy related performance indicators.

Engineering Workflow for Probabilistic Assisted History Matching and Production Forecating: Application to a Middle East Carbonate Reservoir

Abstract: Traditional reconciliation of geomodels with production data is one of the most laborious tasks in reservoir engineering. The uncertainty associated with the great majority of model variables only adds to the overall complexity. This paper introduces an engineering workflow for probabilistic assisted history matching that captures inherent model uncertainty and allows for better quantification of production forecasts. The workflow is applied to history matching of the pilot area in a major, structurally complex Middle East (ME) carbonate reservoir. The simulation model combines 49 wells in five waterflood patterns to match 50 years of oil production and 12 years of water injection and to predict eight years of production. Initially, the reservoir model was calibrated to match oil production by modifying permeability and/or porosity at well locations and by fine-tuning rock-type properties and water saturation. The second level history match implemented two-stage Markov chain Monte Carlo (McMC) stochastic optimization to minimize the misfit in water cut on a well-by-well basis. While relative to evolutionary algorithms or the ensemble Kalman filter (EnKF), the McMC methods provide a statistically rigorous alternative for sampling posterior distribution; when deployed in direct simulation, they impose a high computational cost. The approach presented here accelerates the process by parameterizing the permeability using discrete cosine transform (DCT), constraining the proxy model using streamline-based sensitivities and utilizing parallel and cluster computing. While probabilistic assisted history matching (AHM) successfully reduced the misfit for most producing wells, the computational convergence was sensitive to the level of preserved geological detail. The optimal number of representative history-matched models was identified to capture the uncertainty in reservoir spatial connectivity using rigorous optimization and dynamic model ranking based on forecasted oil recovery factors (ORFs). The reduced set of models minimized the computational load for forecast-based analysis, while retaining the knowledge of the uncertainty in the recovery factor. The comprehensive probabilistic AHM workflow was implemented at the operator’s North Kuwait Integrated Digital Oilfield (KwIDF) collaboration center. It delivers an optimized reservoir model for waterflood management and automatically updates the model quarterly with geological, production, and completion information. This allows engineers to improve the reservoir characterization and identify the areas that require more data capture. Introduction As part of a comprehensive strategy to transform the Kuwait Oil Company (KOC) through the application of digital oilfield (DOF) concepts, KOC initiated an assessment of the major Sabriyah-Mauddud (SaMa) reservoir for conversion to an integrated digital oilfield (iDOF) master platform, with the goal of increasing effectiveness through automating work processes and shortening observation-to-action cycle time. The group of nine first-generation production engineering workflows focuses on production and operational activities and was launched at KwIDF in 2012. The workflows are introduced in Al-Abbasi et al. (2013) and described in greater detail in Al-Jasmi et al. (2013) and references therein. With the vision to drive future KOC operations to the next level of excellence and to realize a large return on the investment in iDOF, the operator’s senior management endorsed the development of a family of advanced integrated asset management (IAM) workflows, referred to as “smartflows,” to optimize and integrate the subsurface models with well models and network surface systems in various time horizons.

Concept of an intelligent production control for global manufacturing in dynamic environments based on rescheduling

Abstract: This paper presents an approach towards an innovative and intelligent production control for a highly flexible and efficient production in an increasingly dynamic and complex environment. For this purpose, an approach is developed on the basis of intelligent rescheduling for global manufacturing networks using information of cyber physical systems.