The Experts below are selected from a list of 294 Experts worldwide ranked by ideXlab platform
Samuel Gomes - One of the best experts on this subject based on the ideXlab platform.
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lean engineering in the Design process an industrial application
MATEC Web of Conferences, 2017Co-Authors: Toufik Boudouh, Samuel GomesAbstract:The objective of this paper is to present a methodology used to streamline the product development process by introducing Lean Engineering concepts. We are interested specifically in Routine Design which represents in some companies more than 80% of the Design activity. A project management model was developed and implemented in a PLM tool. This allows faster initiation of projects in which project planning is automatically performed. Hence, non-added value tasks in project planning were identified and reduced.
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Design Support Based onto Knowledge to Increase Product Reliability and Allow Optimized Abacus Development
Advances in Production Management Systems. Competitive Manufacturing for Innovative Products and Services, 2013Co-Authors: Jérémy Boxberger, Nahdir Lebaal, Samuel Gomes, Daniel Schlegel, Jérémy Boxberger, Samuel GomesAbstract:High competition and low manufacturing costs in emerging countries, force European firms to improve quality, cost and delivery. Research and development departments have to look towards high production Design methods and tools in order to stay competitive. Our research allow to reduce Routine Design process and thereby increase time for added value Design tasks, particularly innovative Design activities. We have applied our methodology onto a roller shutter tube. Existing abacuses are used to define tube deformation, but these abacuses are too restrictive. Our case determine the input information and create a model using our method to create new abacuses more relevant. Our contribution uses the explicit knowledge embedded in a KBE application to co-create or update parametric 3D models with its assembly environment. By implementing this method in an industrial company, we have reduced Routine Design tasks and improved the robustness of the product Design and the product assembly.
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APMS (2) - Design Support Based onto Knowledge to Increase Product Reliability and Allow Optimized Abacus Development
IFIP Advances in Information and Communication Technology, 2013Co-Authors: Jérémy Boxberger, Nahdir Lebaal, Daniel Schlegel, Samuel GomesAbstract:High competition and low manufacturing costs in emerging countries, force European firms to improve quality, cost and delivery. Research and development departments have to look towards high production Design methods and tools in order to stay competitive. Our research allow to reduce Routine Design process and thereby increase time for added value Design tasks, particularly innovative Design activities. We have applied our methodology onto a roller shutter tube. Existing abacuses are used to define tube deformation, but these abacuses are too restrictive. Our case determine the input information and create a model using our method to create new abacuses more relevant. Our contribution uses the explicit knowledge embedded in a KBE application to co-create or update parametric 3D models with its assembly environment. By implementing this method in an industrial company, we have reduced Routine Design tasks and improved the robustness of the product Design and the product assembly.
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Toward an Automatic Reduction of Non-added Values Tasks in the Project-Product-Process Domain
2012Co-Authors: Jérémy Boxberger, Mathieu Lebouteiller, Toufik Boudouh, Samuel GomesAbstract:To increase their competitiveness, companies need to increase the turnover of their products. They should continuously develop attractive new products efficiently in order to increase sales volume and ensure sustainability in globalized markets. The streamlining of Routine engineering processes becomes necessary to improve quality and productivity in Design and allows more time to develop innovative products. The main goal of our contribution is to develop a Design process framework to allow a reduction in Routine Design processes which will thus increase time available for innovative Design processes. The methodology proposed consists of integrating data management, information management, knowledge management, and decision-support methods and tools, such as PDM (product data management), PLM (product lifecycle management), and KBE (Knowledge based engineering). In the area of knowledge management, some methodologies exist to reduce non-added value tasks such as KBE models, Top down Design or Design for X (Design for manufacture, Design for assembly, dis-assembly, etc...). Our methodology deals with the reduction of Routine Design by automatic Design project initiation, including knowledge management. This methodology is tested in a firm specialized in rolling shutter components. This approach allows time reduction of “non-added value tasks” and allows justifying any specification by knowledge and know-how gained in the past. When a new Design project is created, often it will require one or several manufacturing processes to create the product. So, the Designer has to use his own skills and experience to define the task lengths. One issue is how to keep the information usable by every Designer, not only the expert. Another issue is how to preserve the knowledge embedded into the product, the manufacturing process and also in the project. Our contribution uses automatic project initiation, stored in a PLM tool. The automatic generation is based on several models which use configuration containing parameters and knowledge. By introducing a tool using this methodology in an industrial firm, we can reduce Routine Design and improve Design robustness. Additional research will be performed towards an ergonomic use of the tool.
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PLM - Toward an Automatic Reduction of Non-added Values Tasks in the Project-Product-Process Domain
Product Lifecycle Management. Towards Knowledge-Rich Enterprises, 2012Co-Authors: Jérémy Boxberger, Toufik Boudouh, Mathieu Lebouteiller, Samuel Gomes, Jérémy Boxberger, Mathieu Lebouteiller, Toufik Boudouh, Samuel GomesAbstract:To increase their competitiveness, companies need to increase the turnover of their products. They should continuously develop attractive new products efficiently in order to increase sales volume and ensure sustainability in globalized markets. The streamlining of Routine engineering processes becomes necessary to improve quality and productivity in Design and allows more time to develop innovative products. The main goal of our contribution is to develop a Design process framework to allow a reduction in Routine Design processes which will thus increase time available for innovative Design processes. The methodology proposed consists of integrating data management, information management, knowledge management, and decision-support methods and tools, such as PDM (product data management), PLM (product lifecycle management), and KBE (Knowledge based engineering). In the area of knowledge management, some methodologies exist to reduce non-added value tasks such as KBE models, Top down Design or Design for X (Design for manufacture, Design for assembly, dis-assembly, etc...). Our methodology deals with the reduction of Routine Design by automatic Design project initiation, including knowledge management. This methodology is tested in a firm specialized in rolling shutter components. This approach allows time reduction of “non-added value tasks” and allows justifying any specification by knowledge and know-how gained in the past. When a new Design project is created, often it will require one or several manufacturing processes to create the product. So, the Designer has to use his own skills and experience to define the task lengths. One issue is how to keep the information usable by every Designer, not only the expert. Another issue is how to preserve the knowledge embedded into the product, the manufacturing process and also in the project. Our contribution uses automatic project initiation, stored in a PLM tool. The automatic generation is based on several models which use configuration containing parameters and knowledge. By introducing a tool using this methodology in an industrial firm, we can reduce Routine Design and improve Design robustness. Additional research will be performed towards an ergonomic use of the tool.
John S Gero - One of the best experts on this subject based on the ideXlab platform.
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Modeling Creativity and Knowledge-Based Creative Design
2013Co-Authors: John S Gero, Mary Lou MaherAbstract:Over the last decade research into Design processes utilizing ideas and models drawn from artificial intelligence has resulted in a better understanding of Design -- particularly Routine Design -- as a process. Indeed, most of the current research activity directly or indirectly deals only with Routine Design. Not surprisingly, many practicing Designers state that the level of understanding represented by these models is only of mild interest because they fail to embody any ideas about creativity. This volume provides a set of chapters in the areas of modeling creativity and knowledge-based creative Design that examines the potential role and form of computer-aided Design which supports creativity. It aims to define the state-of-the-art of computational creativity in Design as well as to identify research directions. Published at a time when the field of computational creativity in Design is still immature, it should influence the directions of growth and assist the field in reaching maturity.
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an exploration based evolutionary model of a generative Design process
Computer-aided Civil and Infrastructure Engineering, 1996Co-Authors: John S Gero, Vladimir KazakovAbstract:: An exploration-based generative model of Design is proposed. Shape grammars are used as a framework for the knowledge representation within this model. The Routine Design problem over the state space generated using a fixed shape grammar and the creative Design problem over the extended state space generated by using an extended shape grammar—the family of shape grammars which includes the original one—are formulated. Two evolutionary algorithms that produce superior Designs and shape grammars are presented. In the first method, exploration and search processes occur simultaneously whereas in the second they are explicitly separated.
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Learning representations for creative Design using evolution
Artificial Intelligence for Engineering Design Analysis and Manufacturing, 1996Co-Authors: Thorsten Schnier, John S GeroAbstract:Creative Design has been characterized in computational terms as “that Design activity which occurs when a new variable is introduced into the Design” (Gero, 1994). This is opposed to “Routine Design,” where “knowledge about variables, objectives expressed in terms of those variables, constraints expressed in terms of those variables, and the processes needed to find values for those variables, are all known a priori .” A third alternative, “innovative Design,” occurs when no new variables are introduced, but when one or more variables are used with values outside the usual scope. In computational terms, Routine Design can also be seen as “search,” (sometimes also called “exploitation”) in so far as a certain, predefined search space is searched for a Design solution. For creative Design, where the search proceeds outside the boundaries of a predefined search space, the term “exploration” can be used.
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Prober—A Design System Based on Design Prototypes
Artificial Intelligence in Design ’92, 1992Co-Authors: K. W. Tham, John S GeroAbstract:A knowledge-based Design system for Routine Design, acronymed PROBER, is described. PROBER assists Routine Design by drawing on Design prototypes which have recently been proposed as schemas for capturing Design knowledge integrally and comprehensively. By appealing to Design prototypes, PROBER supports Design commencement, continuation and exploration. Underlying PROBER is a process model of Design which focuses on reasoning among function, behaviour and structure. The architecture of PROBER and its implementation are presented in detail.
Jon Sticklen - One of the best experts on this subject based on the ideXlab platform.
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the Routine Design modular distributed modeling platform for distributed Routine Design and simulation based testing of distributed assemblies
Ai Edam Artificial Intelligence for Engineering Design Analysis and Manufacturing, 2008Co-Authors: Taner M Eskil, Jon Sticklen, Clark J. RadcliffeAbstract:In this paper we describe a conceptual framework and implementation of a tool that supports task-directed, distributed Routine Design (RD) augmented with simulation-based Design testing. In our research, we leverage the modular distributed modeling (MDM) methodology to simulate the interaction of Design components in an assembly. The major improvement we have made in the RD methodology is to extend it with the capabilities of incorporating remotely represented off-the-shelf components in Design and simulation-based testing of a distributed assembly. The deliverable of our research is the RD-MDM platform, which is capable of automatically selecting intellectually protected off the shelf Design components over the Internet, integrating these components in an assembly, running simulations for Design testing, and publishing the approved Design without disclosing the proprietary information.
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The Routine Design–modular distributed modeling platform for distributed Routine Design and simulation-based testing of distributed assemblies
Artificial Intelligence for Engineering Design Analysis and Manufacturing, 2007Co-Authors: Mustafa Taner Eskil, Jon Sticklen, Clark J. RadcliffeAbstract:In this paper we describe a conceptual framework and implementation of a tool that supports task-directed, distributed Routine Design (RD) augmented with simulation-based Design testing. In our research, we leverage the modular distributed modeling (MDM) methodology to simulate the interaction of Design components in an assembly. The major improvement we have made in the RD methodology is to extend it with the capabilities of incorporating remotely represented off-the-shelf components in Design and simulation-based testing of a distributed assembly. The deliverable of our research is the RD-MDM platform, which is capable of automatically selecting intellectually protected off the shelf Design components over the Internet, integrating these components in an assembly, running simulations for Design testing, and publishing the approved Design without disclosing the proprietary information.
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Distributed Routine Design over the internet with cooperating mdm agents
2004Co-Authors: Jon Sticklen, Mustafa Taner EskilAbstract:The availability of reliable, high-speed electronic connectivity enabled collaborative Design teams function irrespective of physical distance. But the advent of the Internet has not as yet given rise to a simulation environment that leverages the inherent advantages offered while observing basic constraints imposed by the current wired world, most notably practical limitations on the amount of network traffic. The changes in the procurement process of enterprises need to be reflected in a new type of Design and simulation environment—one that facilitates automated searching and locating of satisfying and optimizing parts, integration of selected parts in an assembly, and simulation of the overall Design that is distributed over the Internet. Our goal is to develop an automated and distributed scheme for Design and simulation of engineering artifacts, in the context of open and competitive e-commerce. With the realization of our goal, Designers will be able to automatically incorporate distributed off-the-shelf parts into their Designs, simulate them as integrated components of the end product, and make their final Designs available to prospective buyers without disclosing proprietary information. In this dissertation we describe a conceptual framework and implementation that supports task directed, distributed Multiple Routine Design augmented with simulation-based Design testing. In our research, we leverage the Modular Distributed Modeling (MDM) methodology to simulate the interaction of Design components in a distributed assembly. The major extension we have made to the overall methodology of Routine Design is to extend it with the capabilities of incorporating remotely represented off-the-shelf components in Design and simulation based testing of a distributed assembly. The deliverable of our research is a conceptual framework and implementation of a distributed multiple Routine Design platform (RD-MDM) that is capable of automated multi-attribute search for remotely represented off-the-shelf Design components, Design parameterization by choosing suitable components for the Design, integrating these components in an assembly, running simulations for testing the total Design, and publishing the approved Design as an MDM agent.
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Multiple Design: An Extension of Routine Design for Generating Multiple Design Alternatives
Artificial Intelligence in Design ’94, 1994Co-Authors: Ahmed Kamel, Jon Sticklen, James K. McdowellAbstract:Many engineering Design situations require the generation of multiple Designs to meet a common set of specifications. This research introduces an effective approach for generating multiple Designs. The method developed utilizes and builds on the generic task approach to knowledge-based systems, as well as the specific Design technique, known as Routine Design.
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Fabricating composite materials-a comprehensive problem-solving architecture based on generic tasks
IEEE Expert, 1992Co-Authors: Jon Sticklen, Ahmed Kamel, Martin C. Hawley, Valerie AdegbiteAbstract:A problem-solving architecture that addresses the entire life cycle of composite-materials fabrication from a generic-task viewpoint is presented. Prototype systems that capture the experience-based static Design of fabrication plans and the progress-control knowledge of cavity tuning for the microwave curing of composites are described. The capturing of compiled process planning in the plan Design phase, the Routine-Design system, and monitoring, global replanning, and local reactive planning of the fabrication plan are discussed. >
Jérémy Boxberger - One of the best experts on this subject based on the ideXlab platform.
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Design Support Based onto Knowledge to Increase Product Reliability and Allow Optimized Abacus Development
Advances in Production Management Systems. Competitive Manufacturing for Innovative Products and Services, 2013Co-Authors: Jérémy Boxberger, Nahdir Lebaal, Samuel Gomes, Daniel Schlegel, Jérémy Boxberger, Samuel GomesAbstract:High competition and low manufacturing costs in emerging countries, force European firms to improve quality, cost and delivery. Research and development departments have to look towards high production Design methods and tools in order to stay competitive. Our research allow to reduce Routine Design process and thereby increase time for added value Design tasks, particularly innovative Design activities. We have applied our methodology onto a roller shutter tube. Existing abacuses are used to define tube deformation, but these abacuses are too restrictive. Our case determine the input information and create a model using our method to create new abacuses more relevant. Our contribution uses the explicit knowledge embedded in a KBE application to co-create or update parametric 3D models with its assembly environment. By implementing this method in an industrial company, we have reduced Routine Design tasks and improved the robustness of the product Design and the product assembly.
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APMS (2) - Design Support Based onto Knowledge to Increase Product Reliability and Allow Optimized Abacus Development
IFIP Advances in Information and Communication Technology, 2013Co-Authors: Jérémy Boxberger, Nahdir Lebaal, Daniel Schlegel, Samuel GomesAbstract:High competition and low manufacturing costs in emerging countries, force European firms to improve quality, cost and delivery. Research and development departments have to look towards high production Design methods and tools in order to stay competitive. Our research allow to reduce Routine Design process and thereby increase time for added value Design tasks, particularly innovative Design activities. We have applied our methodology onto a roller shutter tube. Existing abacuses are used to define tube deformation, but these abacuses are too restrictive. Our case determine the input information and create a model using our method to create new abacuses more relevant. Our contribution uses the explicit knowledge embedded in a KBE application to co-create or update parametric 3D models with its assembly environment. By implementing this method in an industrial company, we have reduced Routine Design tasks and improved the robustness of the product Design and the product assembly.
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Toward an Automatic Reduction of Non-added Values Tasks in the Project-Product-Process Domain
2012Co-Authors: Jérémy Boxberger, Mathieu Lebouteiller, Toufik Boudouh, Samuel GomesAbstract:To increase their competitiveness, companies need to increase the turnover of their products. They should continuously develop attractive new products efficiently in order to increase sales volume and ensure sustainability in globalized markets. The streamlining of Routine engineering processes becomes necessary to improve quality and productivity in Design and allows more time to develop innovative products. The main goal of our contribution is to develop a Design process framework to allow a reduction in Routine Design processes which will thus increase time available for innovative Design processes. The methodology proposed consists of integrating data management, information management, knowledge management, and decision-support methods and tools, such as PDM (product data management), PLM (product lifecycle management), and KBE (Knowledge based engineering). In the area of knowledge management, some methodologies exist to reduce non-added value tasks such as KBE models, Top down Design or Design for X (Design for manufacture, Design for assembly, dis-assembly, etc...). Our methodology deals with the reduction of Routine Design by automatic Design project initiation, including knowledge management. This methodology is tested in a firm specialized in rolling shutter components. This approach allows time reduction of “non-added value tasks” and allows justifying any specification by knowledge and know-how gained in the past. When a new Design project is created, often it will require one or several manufacturing processes to create the product. So, the Designer has to use his own skills and experience to define the task lengths. One issue is how to keep the information usable by every Designer, not only the expert. Another issue is how to preserve the knowledge embedded into the product, the manufacturing process and also in the project. Our contribution uses automatic project initiation, stored in a PLM tool. The automatic generation is based on several models which use configuration containing parameters and knowledge. By introducing a tool using this methodology in an industrial firm, we can reduce Routine Design and improve Design robustness. Additional research will be performed towards an ergonomic use of the tool.
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PLM - Toward an Automatic Reduction of Non-added Values Tasks in the Project-Product-Process Domain
Product Lifecycle Management. Towards Knowledge-Rich Enterprises, 2012Co-Authors: Jérémy Boxberger, Toufik Boudouh, Mathieu Lebouteiller, Samuel Gomes, Jérémy Boxberger, Mathieu Lebouteiller, Toufik Boudouh, Samuel GomesAbstract:To increase their competitiveness, companies need to increase the turnover of their products. They should continuously develop attractive new products efficiently in order to increase sales volume and ensure sustainability in globalized markets. The streamlining of Routine engineering processes becomes necessary to improve quality and productivity in Design and allows more time to develop innovative products. The main goal of our contribution is to develop a Design process framework to allow a reduction in Routine Design processes which will thus increase time available for innovative Design processes. The methodology proposed consists of integrating data management, information management, knowledge management, and decision-support methods and tools, such as PDM (product data management), PLM (product lifecycle management), and KBE (Knowledge based engineering). In the area of knowledge management, some methodologies exist to reduce non-added value tasks such as KBE models, Top down Design or Design for X (Design for manufacture, Design for assembly, dis-assembly, etc...). Our methodology deals with the reduction of Routine Design by automatic Design project initiation, including knowledge management. This methodology is tested in a firm specialized in rolling shutter components. This approach allows time reduction of “non-added value tasks” and allows justifying any specification by knowledge and know-how gained in the past. When a new Design project is created, often it will require one or several manufacturing processes to create the product. So, the Designer has to use his own skills and experience to define the task lengths. One issue is how to keep the information usable by every Designer, not only the expert. Another issue is how to preserve the knowledge embedded into the product, the manufacturing process and also in the project. Our contribution uses automatic project initiation, stored in a PLM tool. The automatic generation is based on several models which use configuration containing parameters and knowledge. By introducing a tool using this methodology in an industrial firm, we can reduce Routine Design and improve Design robustness. Additional research will be performed towards an ergonomic use of the tool.
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Creative Design Opportunities into Knowledge Based Engineering Process
2012Co-Authors: Jérémy Boxberger, Mathieu Lebouteiller, D. Schlegeld, N. Lebaaln, Samuel GomesAbstract:High competition and low manufacturing costs in emerging countries, forces European firms to improve quality, cost and delivery. In this context, research and development departments have to look towards high production Design methods and tools in order to stay competitive. The main goal of our research is to reduce Routine Design process and thereby increase time for creative Design tasks, particularly, creative Design in new concept creation, optimisation and validation, by integrating data management, information management, knowledge management, and decision-support methods and tools, such as PDM (product data management), PLM (product life management), KBE (Knowledge based engineering), etc. Our methodology deals with reduction of Routine Design activities by introducing automatic activities during project, product and process Design tasks in order to generate time for creative Design. A 3D model generated by KBE tools is able to make new concepts crossing different parameters together, then the new concepts are automaticaly checked by validation loops, including product validation and process validation. Our methodology is tested in a firm specialized in shutter components. By implementing this method in an industrial company, we can reduce Routine Design, improve the Design robustness and also take the opportunity to try new concepts, materials, combinations and at the same time implement new knowledge for future concepts.
F.j.a.m. Van Houten - One of the best experts on this subject based on the ideXlab platform.
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Modeling the Structure and Complexity of Engineering Routine Design Problems
2011Co-Authors: Juan Manuel Jauregui Becker, Wessel Willems Wits, F.j.a.m. Van HoutenAbstract:This paper proposes a model to structure Routine Design problems as well as a model of its Design complexity. The idea is that having a proper model of the structure of such problems enables understanding its complexity, and likewise, a proper understanding of its complexity enables the development of systematic approaches to solve them. The end goal is to develop computer systems capable of taking over Routine Design tasks based on generic and systematic solving approaches. It is proposed to structure Routine Design in three main states: problem class, problem instance, and problem solution. Design complexity is related to the degree of uncertainty in knowing how to move a Design problem from one state to another. Axiomatic Design Theory is used as reference for understanding complexity in Routine Design.
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TOWARD A PRACTICAL GUIDE TO KNOWLEDGE ENGINEERING FOR PARAMETRIC Routine Design
2010Co-Authors: W.o. Schotborgh, Frans Kokkeler, C. A. Mcmahon, F.j.a.m. Van HoutenAbstract:This paper proposes a methodological approach to knowledge acquisition and modelling. The source of the knowledge is considered to be an expert Designer. The content of this paper focuses on the knowledge acquisition phase, which includes a method to interview an expert to obtain a model of his/her experience-based knowledge in a systematic manner. A model of the Design process and synthesis knowledge is used as guideline. The scope is parametric Design with available knowledge: Routine variant and adaptive Design.
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Structure and models of artifactual Routine Design problems for computational synthesis
CIRP Journal of Manufacturing Science and Technology, 2009Co-Authors: Juan Manuel Jauregui Becker, Hans Tragter, F.j.a.m. Van HoutenAbstract:Computational synthesis (CS) researches the automatic generation of solutions to Design problems. The aim is to shorten Design times and present the user with multiple Design solutions. However, initializing a new CS process has not received much attention in literature. With this motivation, this paper presents a framework to structure and model Routine Design to assist the development of new CS processes. First, concepts are presented and used to propose a structure for artifactual Routine Design problems. Latter, base models (building blocks) for creating new Designs are described. Finally, a classification of Design families according to its structure and models is presented together with its relation to know CS methods.
