Design of a Control System for a Reconfigurable Engine Assembly Line

Today’s automotive manufacturing environment is dynamic. It is characterized by short life cycles of products especially in powertrain, due in part to changing Government regulations for fuel economy. In the USA, the National Highway Traffic and Safety Administration (NHTSA), Corporate Average Fuel Economy (CAFE) mandates an average of 29 miles per gallon (mpg), gradually increasing to 35.5 mpg by 2016 and 54.5 mpg towards 2025. Life cycles of engines and transmissions have consequently shortened, driving automakers to develop and manufacture more efficient powertrains. Not long ago, plants produced engines for decades, with minor modifications warranting slight manufacturing line rework. Conversely, today’s changing trends require machines and complete engine line overhauls rendering initial setups obsolete. Automakers compete to satisfy government regulations for best mileage and also lower manufacturing cost, thus the adoption of Reconfigurable Manufacturing Systems (RMS). Production lines follow modularity in designs, for hardware and software, to adapt to new business conditions, economically and time-wise. Information Technology (IT) and Controls are growing closer with the line of demarcation disappearing in manufacturing. Controls are benefiting from opportunities in IT, hardware and software. The advent of agent-based technology which are autonomous, cooperative and extendible in different production activities, helped to develop controls for RMS in academia. Component-based software suitable for RMS modularity and plug-and-play hardware/software components has gained decades of popularity in the software industry. This thesis implements distributed controls imbedding component-based technology and IEC 61311-3 function block standard for automotive engine assembly, which will contribute to these developments. The control architecture provides reconfigurability which is lacking in current manufacturing systems. The research imbeds: 1- Reconfigurability - Fitting RMS-designed hardware towards new manufacturing, 2- Reusability - Building software library for reuse across assembly lines, and 3- Plug-and-Play - Embedding easy to assemble software components (function blocks)

Generic Design Methodology for Smart Manufacturing Systems From a Practical Perspective. Part II—Systematic Designs of Smart Manufacturing Systems

In a traditional system paradigm, an enterprise reference model provides the guide for practitioners to select manufacturing elements, configure elements into a manufacturing system, and model system options for evaluation and comparison of system solutions against given performance metrics. However, a smart manufacturing system aims to reconfigure different systems in achieving high-level smartness in its system lifecycle; moreover, each smart system is customized in terms of the constraints of manufacturing resources and the prioritized performance metrics to achieve system smartness. Few works were found on the development of systematic methodologies for the design of smart manufacturing systems. The novel contributions of the presented work are at two aspects: (1) unified definitions of digital functional elements and manufacturing systems have been proposed; they are generalized to have all digitized characteristics and they are customizable to any manufacturing system with specified manufacturing resources and goals of smartness and (2) a systematic design methodology has been proposed; it can serve as the guide for designs of smart manufacturing systems in specified applications. The presented work consists of two separated parts. In the first part of paper, a simplified definition of smart manufacturing (SM) is proposed to unify the diversified expectations and a newly developed concept digital triad (DT-II) is adopted to define a generic reference model to represent essential features of smart manufacturing systems. In the second part of the paper, the axiomatic design theory (ADT) is adopted and expanded as the generic design methodology for design, analysis, and assessment of smart manufacturing systems. Three case studies are reviewed to illustrate the applications of the proposed methodology, and the future research directions towards smart manufacturing are discussed as a summary in the second part

Design of a Scalable Modular Production System for a Two-stage Food Service Franchise System

The geographically distributed production of fresh food poses unique challenges to the production system design because of their stringent industry and logistics requirements. The purpose of this research is to examine the case of a European fresh food manufacturer’s approach to introduce a scalable modular production concept for an international two‐stage gastronomy franchise system in order to identify best practice guidelines and to derive a framework for the design of distributed production systems that perform in a highly dynamic environment. The design framework was developed by creating a theoretical model through literature review and the thorough analysis of an industrial case. Information was collected through multiple site visits, workshops and semi‐structured interviews with the company’s key staff of the project, as well as examination of relevant company documentations. By means of a scenario for the Central European market, the model was reviewed in terms of its development potential and finally approved for implementation. However, research through case survey requires further empirical investigation to fully establish this approach as a valid and reliable design tool

Summer school on intelligent agents in automation: Experience and reflections from the second edition

Several research agendas worldwide are targeting the development of Industrial Cyber-physical Systems as the next generation of intelligent embedded devices with improved interaction capabilities. These devices, and their potential uses, are though to deliver a radical increase in system sustainability, reconfigurability and flexibility which is perceived to be the root of the so called 4 th Industrial Revolution. However such technical systems, at the envisioned revolutionary scale, do not exist just yet and require a convergent and multidisciplinary research and development efforts. The academia curricula are also, albeit slowly, adjusting to the emerging education requirements. The Summer School on Intelligent Agents in Automation is a joint effort from several researchers in core areas of the 4 th Industrial Revolution landscape to close the gap and promote advanced education in this context. This paper describes the implementation of the 2 nd edition of the event as well as the experience and reflections resultant from it.info:eu-repo/semantics/publishedVersio

Architecting a System Model for Personalized Healthcare Delivery and Managed Individual Health Outcomes

In recent years, healthcare needs have shifted from treating acute conditions to meeting an unprecedented chronic disease burden. The healthcare delivery system has structurally evolved to address two primary features of acute care: the relatively short time period, on the order of a patient encounter, and the siloed focus on organs or organ systems, thereby operationally fragmenting and providing care by organ specialty. Much more so than acute conditions, chronic disease involves multiple health factors with complex interactions between them over a prolonged period of time necessitating a healthcare delivery model that is personalized to achieve individual health outcomes. Using the current acute-based healthcare delivery system to address and provide care to patients with chronic disease has led to significant complexity in the healthcare delivery system. This presents a formidable systems’ challenge where the state of the healthcare delivery system must be coordinated over many years or decades with the health state of each individual that seeks care for their chronic conditions. This paper architects a system model for personalized healthcare delivery and managed individual health outcomes. To ground the discussion, the work builds upon recent structural analysis of mass-customized production systems as an analogous system and then highlights the stochastic evolution of an individual’s health state as a key distinguishing feature

Coordination Of Hierarchical Command And Control Services

The purpose of this program is to show emerging information technologies can significantly improve key areas of tactical operations, resulting in the conversion of software developed under the ATO to existing battlefield systems. One such key area is Information Dissemination and Management (ID&M). The key software that will be developed under the ID&M portion requires a collection of agent-based software services that will collaborate during tactical mission planning and execution

Fusion of Information and Analytics: A Discussion on Potential Methods to Cope with Uncertainty in Complex Environments (Big Data and IoT)

International audienceInformation overload and complexity are core problems to most organizations of today. The advances in networking capabilities have created the conditions of complexity by enabling richer, real-time interactions between and among individuals, objects, systems and organizations. Fusion of Information and Analytics Technologies (FIAT) are key enablers for the design of current and future decision support systems to support prognosis, diagnosis, and prescriptive tasks in such complex environments. Hundreds of methods and technologies exist, and several books have been dedicated to either analytics or information fusion so far. However, very few have discussed the methodological aspects and the need of integrating frameworks for these techniques coming from multiple disciplines. This paper presents a discussion of potential integrating frameworks as well as the development of a computational model to evolve FIAT-based systems capable of meeting the challenges of complex environments such as in Big Data and Internet of Things (IoT)

Capability-based adaptation of production systems in a changing environment

Today’s production systems have to cope with volatile production environments characterized by frequently changing customer requirements, an increasing number of product variants, small batch sizes, short product life-cycles, the rapid emergence of new technical solutions and increasing regulatory requirements aimed at sustainable manufacturing. These constantly changing requirements call for adaptive and rapidly responding production systems that can adjust to the required changes in processing functions, production capacity and the distribution of the orders. This adaptation is required on the physical, logical and parametric levels. Such adaptivity cannot be achieved without intelligent methodologies, information models and tools to facilitate the adaptation planning and reactive adaptation of the systems. In industry it has been recognized that, because of the often expensive and inefficient adaptation process, companies rarely decide to adapt their production lines. This is mainly due to a lack of sufficient information and documentation about the capabilities of the current system and its lifecycle, as well as a lack of detailed methods for planning the adaptation, which makes it impossible to accurately estimate its scale and cost. Currently, the adaptation of production systems is in practice a human driven process, which relies strongly on the expertise and tacit knowledge of the system integrators or the end-user of the system. This thesis develops a capability-based, computer-aided adaptation methodology, which supports both the human-controlled adaptation planning and the dynamic reactive adaptation of production systems. The methodology consists of three main elements. The first element is the adaptation schema, which illustrates the activities and information flows involved in the overall adaptation planning process and the resources used to support the planning. The adaptation schema forms the backbone of the methodology, guiding the use of other developed elements during both the adaptation planning and reactive adaptation. The second element, which is actually the core of the developed methodology, is the formal ontological resource description used to describe the resources based on their capabilities. The overall resource description utilizes a capability model, which divides the capabilities into simple and combined capabilities. The resources are assigned the simple capabilities they possess. When multiple resources are co-operating, their combined capability can be reasoned out based on the associations defined in the capability model. The adaptation methodology is based on the capability-based matching of product requirements and available system capabilities in the context of the adaptation process. Thus, the third main element developed in this thesis is the framework and rules for performing this capability matching. The approach allows automatic information filtering and the generation of system configuration scenarios for the given requirements, thus facilitating the rapid allocation of resources and the adaptation of systems. Human intelligence is used to validate the automatically-generated scenarios and to select the best one, based on the desired criteria. Based on these results, an approach to evaluating the compatibility of an existing production system with different product requirements has been formulated. This approach evaluates the impact any changes in these requirements may have on the production system. The impact of the changes is illustrated in the form of compatibility graphs, which enable comparison between different product scenarios in terms of the effort required to implement the system adaptation, and the extent to which the current system can be utilized to meet the new requirements. It thus aids in making decisions regarding product and production strategies and adaptation