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

Working Notes from the 1992 AAAI Spring Symposium on Practical Approaches to Scheduling and Planning

The symposium presented issues involved in the development of scheduling systems that can deal with resource and time limitations. To qualify, a system must be implemented and tested to some degree on non-trivial problems (ideally, on real-world problems). However, a system need not be fully deployed to qualify. Systems that schedule actions in terms of metric time constraints typically represent and reason about an external numeric clock or calendar and can be contrasted with those systems that represent time purely symbolically. The following topics are discussed: integrating planning and scheduling; integrating symbolic goals and numerical utilities; managing uncertainty; incremental rescheduling; managing limited computation time; anytime scheduling and planning algorithms, systems; dependency analysis and schedule reuse; management of schedule and plan execution; and incorporation of discrete event techniques

An agile and adaptive holonic architecture for manufacturing control

Tese de doutoramento. Engenharia Electrotécnica e de Computadores. 2004. Faculdade de Engenharia. Universidade do Port

An experiment in remote manufacturing using the advanced communications technology satellite

The goal of the completed project was to develop an experiment in remote manufacturing that would use the capabilities of the ACTS satellite. A set of possible experiments that could be performed using the Advanced Communications Technology Satellite (ACTS), and which would perform remote manufacturing using a laser cutter and an integrated circuit testing machine are described in detail. The proposed design is shown to be a feasible solution to the offered problem and it takes into consideration the constraints that were placed on the experiment. In addition, we have developed two more experiments that are included in this report: backup of rural telecommunication networks, and remote use of Synthetic Aperture Radar (SAR) data analysis for on-site collection of glacier scattering data in the Antarctic

The evolution of cell formation problem methodologies based on recent studies (1997-2008): review and directions for future research

This paper presents a literature review of the cell formation (CF) problem concentrating on formulations proposed in the last decade. It refers to a number of solution approaches that have been employed for CF such as mathematical programming, heuristic and metaheuristic methodologies and artificial intelligence strategies. A comparison and evaluation of all methodologies is attempted and some shortcomings are highlighted. Finally, suggestions for future research are proposed useful for CF researchers

Internet of robotic things : converging sensing/actuating, hypoconnectivity, artificial intelligence and IoT Platforms

The Internet of Things (IoT) concept is evolving rapidly and influencing newdevelopments in various application domains, such as the Internet of MobileThings (IoMT), Autonomous Internet of Things (A-IoT), Autonomous Systemof Things (ASoT), Internet of Autonomous Things (IoAT), Internetof Things Clouds (IoT-C) and the Internet of Robotic Things (IoRT) etc.that are progressing/advancing by using IoT technology. The IoT influencerepresents new development and deployment challenges in different areassuch as seamless platform integration, context based cognitive network integration,new mobile sensor/actuator network paradigms, things identification(addressing, naming in IoT) and dynamic things discoverability and manyothers. The IoRT represents new convergence challenges and their need to be addressed, in one side the programmability and the communication ofmultiple heterogeneous mobile/autonomous/robotic things for cooperating,their coordination, configuration, exchange of information, security, safetyand protection. Developments in IoT heterogeneous parallel processing/communication and dynamic systems based on parallelism and concurrencyrequire new ideas for integrating the intelligent “devices”, collaborativerobots (COBOTS), into IoT applications. Dynamic maintainability, selfhealing,self-repair of resources, changing resource state, (re-) configurationand context based IoT systems for service implementation and integrationwith IoT network service composition are of paramount importance whennew “cognitive devices” are becoming active participants in IoT applications.This chapter aims to be an overview of the IoRT concept, technologies,architectures and applications and to provide a comprehensive coverage offuture challenges, developments and applications

Advancing automation and robotics technology for the Space Station and for the US economy. Volume 1: Executive overview

In response to Public Law 98-371, dated July 18, 1984, the NASA Advanced Technology Advisory Committee has studied automation and robotics for use in the Space Station. The Executive Overview, Volume 1 presents the major findings of the study and recommends to NASA principles for advancing automation and robotics technologies for the benefit of the Space Station and of the U.S. economy in general. As a result of its study, the Advanced Technology Advisory Committee believes that a key element of technology for the Space Station is extensive use of advanced general-purpose automation and robotics. These systems could provide the United States with important new methods of generating and exploiting space knowledge in commercial enterprises and thereby help preserve U.S. leadership in space

Analysis of manufacturing operations using knowledge- Enriched aggregate process planning

Knowledge-Enriched Aggregate Process Planning is concerned with the problem of supporting agile design and manufacture by making process planning feedback integral to the design function. A novel Digital Enterprise Technology framework (Maropoulos 2003) provides the technical context and is the basis for the integration of the methods with existing technologies for enterprise-wide product development. The work is based upon the assertion that, to assure success when developing new products, the technical and qualitative evaluation of process plans must be carried out as early as possible. An intelligent exploration methodology is presented for the technical evaluation of the many alternative manufacturing options which are feasible during the conceptual and embodiment design phases. 'Data resistant' aggregate product, process and resource models are the foundation of these planning methods. From the low-level attributes of these models, aggregate methods to generate suitable alternative process plans and estimate Quality, Cost and Delivery (QCD) have been created. The reliance on QCD metrics in process planning neglects the importance of tacit knowledge that people use to make everyday decisions and express their professional judgement in design. Hence, the research also advances the core aggregate planning theories by developing knowledge-enrichment methods for measuring and analysing qualitative factors as an additional indicator of manufacturing performance, which can be used to compute the potential of a process plan. The application of these methods allows the designer to make a comparative estimation of manufacturability for design alternatives. Ultimately, this research should translate into significant reductions in both design costs and product development time and create synergy between the product design and the manufacturing system that will be used to make it. The efficacy of the methodology was proved through the development of an experimental computer system (called CAPABLE Space) which used real industrial data, from a leading UK satellite manufacturer to validate the industrial benefits and promote the commercial exploitation of the research

Aggregate process planning and manufacturing assessment for concurrent engineering

The introduction of concurrent engineering has led to a need to perform product development tasks with reduced information detail. Decisions taken during the early design stages will have the greatest influence on the cost of manufacture. The manufacturing requirements for alternative design options should therefore be considered at this time. Existing tools for product manufacture assessment are either too detailed, requiring the results of detailed design information, or too abstract, unable to consider small changes in design configuration. There is a need for an intermediate level of assessment which will make use of additional design detail where available, whilst allowing assessment of early designs. This thesis develops the concept of aggregate process planning as a methodology for supporting concurrent engineering. A methodology for performing aggregate process planning of early product designs is presented. Process and resources alternatives are identified for each feature of the component and production plans are generated from these options. Alternative production plans are assessed in terms of cost, quality and production time. A computer based system (CESS, Concurrent Engineering Support System) has been developed to implement the proposed methodology. The system employs object oriented modelling techniques to represent designs, manufacturing resources and process planning knowledge. A product model suitable for the representation of component designs at varying levels of detail is presented. An aggregate process planning functionality has been developed to allow the generation of sets of alternative plans for a component in a given factory. Manufacturing cost is calculated from the cost of processing, set-ups, transport, material and quality. Processing times are calculated using process specific methods which are based on standard cutting data. Process quality cost is estimated from a statistical analysis of historical SPC data stored for similar operations performed in the factory, where available. The aggregate process planning functionality has been tested with example component designs drawn from industry

NASA space station automation: AI-based technology review

Research and Development projects in automation for the Space Station are discussed. Artificial Intelligence (AI) based automation technologies are planned to enhance crew safety through reduced need for EVA, increase crew productivity through the reduction of routine operations, increase space station autonomy, and augment space station capability through the use of teleoperation and robotics. AI technology will also be developed for the servicing of satellites at the Space Station, system monitoring and diagnosis, space manufacturing, and the assembly of large space structures