Ontology-based module selection in the design of reconfigurable machine tools

Reconfigurable machine tools (RMTs) are important equipment for enterprises to cope with ever-changing markets because of their flexibility. In design of such equipment, selection of appropriate modules is a very critical decision factor to effectively and efficiently satisfy manufacturing requirements. However, the selection of appropriate modules is a challenging task because it is a multi-domain mapping process relying heavily on experts’ domain knowledge, which is usually unstructured and implicit. To effectively support RMT designers, an ontology-based RMT module selection method is proposed. First, a knowledge base is built by development of an ontology to formally represent the taxonomy, properties, and causal relationships of/among three domain core concepts, namely, machining feature , machining operation , and RMT module involved in RMT design. Second, a four-step sequential procedure is established to facilitate the utilization of encoded knowledge from a knowledge base to aid in the selection of appropriate RMT modules. The procedure takes a given part family as the input, automatically infers the required machining operations as well as the RMT modules through rule-based reasoning, and eventually forms a set of RMT configurations that are capable of machining the part family as the output. Finally, the efficacy of the ontology-based RMT module selection method is demonstrated using a plate family manufacturing example. Results show that the approach is effective to support designers by appropriately and rapidly selecting modules and generating configurations in RMT design.

[1]  Lilan Liu,et al.  A Method for Design of Modular Reconfigurable Machine Tools , 2017 .

[2]  Z. M. Bi,et al.  Concurrent optimal design of modular robotic configuration , 2001 .

[3]  Samir Lamouri,et al.  Ontology for cloud manufacturing based Product Lifecycle Management , 2019, J. Intell. Manuf..

[4]  Zhuming Bi,et al.  Development and Control of a 5-Axis Reconfigurable Machine Tool , 2011, J. Robotics.

[5]  Arturo Molina,et al.  Development of an Integrated Approach to the Design of Reconfigurable Micro/Mesoscale CNC Machine Tools , 2014 .

[6]  Lalit Patil,et al.  Digital manufacturing market: a semantic web-based framework for agile supply chain deployment , 2010, Journal of Intelligent Manufacturing.

[7]  L. X. Fan,et al.  Axiomatic design theory: further notes and its guideline to applications , 2015 .

[8]  Thomas L. Saaty,et al.  Multicriteria Decision Making: The Analytic Hierarchy Process: Planning, Priority Setting, Resource Allocation , 1990 .

[9]  Khumbulani Mpofu,et al.  A morphology proposal in commercial-off-the-shelf reconfigurable machine tools , 2014 .

[10]  Li Chen,et al.  Optimal Module Selection for Preliminary Design of Reconfigurable Machine Tools , 2005 .

[11]  Sridhar Kota,et al.  Generalized kinematic modeling of Reconfigurable Machine Tools , 2002 .

[12]  Walter Schumacher,et al.  Online Estimation and Correction of Systematic Encoder Line Errors , 2017 .

[13]  Brigitte Chebel-Morello,et al.  A mix method of knowledge capitalization in maintenance , 2008, J. Intell. Manuf..

[14]  C. A. van Luttervelt,et al.  Toward a resilient manufacturing system , 2011 .

[15]  Robert I. M. Young,et al.  The application of common logic based formal ontologies to assembly knowledge sharing , 2015, J. Intell. Manuf..

[16]  Hae-Jin Choi,et al.  Design and dynamic analysis of an arch-type desktop reconfigurable machine , 2010 .

[17]  Ahmet S. Yigit,et al.  Optimal selection of module instances for modular products in reconfigurable manufacturing systems , 2003 .

[18]  Yan Yan,et al.  Formation of part family for reconfigurable manufacturing systems considering bypassing moves and idle machines , 2016 .

[19]  Yan Yan,et al.  Reconfiguration point decision method based on dynamic complexity for reconfigurable manufacturing system (RMS) , 2018, J. Intell. Manuf..

[20]  Ratna Babu Chinnam,et al.  Product design and manufacturing process based ontology for manufacturing knowledge reuse , 2019, J. Intell. Manuf..

[21]  Eeva Järvenpää,et al.  The development of an ontology for describing the capabilities of manufacturing resources , 2018, J. Intell. Manuf..

[22]  Soh-Khim Ong,et al.  An object-oriented approach to computer-aided design of a plastic injection mould , 1995, J. Intell. Manuf..

[23]  Manoj Kumar Tiwari,et al.  An adapted NSGA-2 algorithm based dynamic process plan generation for a reconfigurable manufacturing system , 2012, J. Intell. Manuf..

[24]  Thomas Lorenzer,et al.  Modeling and evaluation tool for supporting decisions on the design of reconfigurable machine tools , 2007 .

[25]  Arend L. Schwab,et al.  Toward a Unified Design Approach for Both Compliant Mechanisms and Rigid-Body Mechanisms: Module Optimization , 2015 .

[26]  Hao Chen,et al.  Imaginal Thinking-Based Human-Machine Design Methodology for the Configuration of Reconfigurable Machine Tools , 2012, IEEE Transactions on Industrial Informatics.

[27]  Xing Chen,et al.  Ontology-based coupled optimisation design method using state-space analysis for the spindle box system of large ultra-precision optical grinding machine , 2017, Enterp. Inf. Syst..

[28]  Nam P. Suh,et al.  principles in design , 1990 .

[29]  Joel C. Huegel,et al.  Design, refinement, implementation and prototype testing of a reconfigurable lathe-mill , 2013 .

[30]  Khumbulani Mpofu Machine Morphology in Reconfigurable Machine Tools , 2012 .

[31]  Camelia Chira,et al.  An agent-based approach to knowledge management in distributed design , 2006, J. Intell. Manuf..

[32]  A. Galip Ulsoy,et al.  Non-commercial Research and Educational Use including without Limitation Use in Instruction at Your Institution, Sending It to Specific Colleagues That You Know, and Providing a Copy to Your Institution's Administrator. All Other Uses, Reproduction and Distribution, including without Limitation Comm , 2022 .

[33]  Vincent Cheutet,et al.  A product design ontology for enhancing shape processing in design workflows , 2009, J. Intell. Manuf..

[34]  Qiang Zhou,et al.  A hybrid fault diagnosis method for mechanical components based on ontology and signal analysis , 2019, J. Intell. Manuf..

[35]  Haibo Hong,et al.  Ontology-based human-machine integrated design method for ultra-precision grinding machine spindle , 2016, J. Ind. Inf. Integr..

[36]  George A. Hazelrigg,et al.  Validation of engineering design alternative selection methods , 2003 .

[37]  Ali Siadat,et al.  Use of a manufacturing ontology and Function- Behaviour-Structure approach for the design of a Reconfigurable Machine Tool , 2008 .

[38]  Ali M. Niknejad,et al.  An ontology supported risk assessment approach for the intelligent configuration of supply networks , 2016, Journal of Intelligent Manufacturing.

[39]  Monica Bordegoni,et al.  An approach to design reconfigurable manufacturing tools to manage product variability: the mass customisation of eyewear , 2018, J. Intell. Manuf..

[40]  Kazuo Furuta,et al.  On domain modelling of the service system with its application to enterprise information systems , 2016, Enterp. Inf. Syst..