Classification and mitigation of uncertainty as per the product design stages: framework and case study

Product design undergoes various stages and each stage requires valid inputs to obtain the desired output(s). Many times, the inputs that are provided are inaccurate or uncertain. Further, the design of a new product normally starts with a limited knowledge and not properly defined targets to convert an idea or concept into a marketable product. The complex and dynamic nature of design leads to uncertainty, which makes taking the right decision critical. Thus, it is felt that there is a serious need to handle uncertainties during product design. This work analyses the sources of uncertainty that may creep in the product design process during different design stages. Besides, it also illustrates the taxonomy of uncertainty and the tools that might be used to mitigate the uncertainty during each design stage. The paper validates the approach with the help of a design example. It is felt that the designers may benefit from this work as they can identify what type of uncertainty may come upon during a particular stage of the design process, along with the tool that can be used to handle the uncertainty in an effective manner.

[1]  Georgia Alexouda,et al.  A user-friendly marketing decision support system for the product line design using evolutionary algorithms , 2005, Decis. Support Syst..

[2]  Danny Miller,et al.  Strategic Responses to Three Kinds of Uncertainty: Product Line Simplicity at the Hollywood Film Studios , 1999 .

[3]  M. Werner,et al.  Satellite Systems for Personal and Broadband Communications , 2000 .

[4]  Nikolaos F. Matsatsinis,et al.  Particle Swarm Optimization for Optimal Product Line Design , 2009 .

[5]  T. Livraghi,et al.  "Wait and see" policy for early hepatocellular carcinoma. , 2013, Journal of hepatology.

[6]  P. van Gelder,et al.  Quantitative fault tree analysis for urban water infrastructure flooding , 2011 .

[7]  Marie-Lise Moullec,et al.  Toward System Architecture Generation and Performances Assessment Under Uncertainty Using Bayesian Networks , 2013 .

[8]  George Mangalaraj,et al.  Challenges of migrating to agile methodologies , 2005, CACM.

[9]  Shana Smith,et al.  A multi-objective modular design method for creating highly distinct independent modules , 2016 .

[10]  Sebastian Sitarz,et al.  Hybrid methods in multi-criteria dynamic programming , 2006, Appl. Math. Comput..

[11]  Xiaoping Du,et al.  Reliability-based multidisciplinary optimization for aircraft wing design , 2006 .

[12]  Mitsuo Nagamachi,et al.  Rule-based inference model for the Kansei Engineering System , 1999 .

[13]  Tyson R. Browning,et al.  Adding value in product development by creating information and reducing risk , 2002, IEEE Trans. Engineering Management.

[14]  Steven D. Eppinger,et al.  Improving product development process design: a method for managing information flows, risks, and iterations , 2011 .

[15]  Candace A. Yano,et al.  Product line selection and pricing under a share-of-surplus choice model , 2003, Eur. J. Oper. Res..

[16]  Farrokh Mistree,et al.  Design for manufacturing: application of collaborative multidisciplinary decision-making methodology , 2007 .

[17]  P. John Clarkson,et al.  Comparison of ilities for protection against uncertainty in system design , 2013 .

[18]  Robert Stone,et al.  The risk in early design method , 2009 .

[19]  Masahiko Hirao,et al.  Decision support tools for environmentally benign process design under uncertainty , 2004, Comput. Chem. Eng..

[20]  Hans-Peter Weikard,et al.  Introduction: Risk and Uncertainty in Environmental and Resource Economics , 2004 .

[21]  John X. Wang,et al.  What Every Engineer Should Know About Risk Engineering and Management , 2000 .

[22]  L. Cooper A research agenda to reduce risk in new product development through knowledge management: a practitioner perspective , 2003 .

[23]  Robert G. Cooper,et al.  Perspective: The Stage‐Gate® Idea‐to‐Launch Process—Update, What's New, and NexGen Systems* , 2008 .

[24]  Stefano Filippi,et al.  The Design Guidelines (DGLs), a knowledge-based system for industrial design developed accordingly to ISO-GPS (Geometrical Product Specifications) concepts , 2007 .

[25]  John E. Renaud,et al.  Uncertainty quantification using evidence theory in multidisciplinary design optimization , 2004, Reliab. Eng. Syst. Saf..

[26]  Luis A. Ricardez-Sandoval,et al.  A methodology for the simultaneous design and control of large-scale systems under process parameter uncertainty , 2011, Comput. Chem. Eng..

[27]  Erik K. Antonsson,et al.  Imprecision in Engineering Design , 1995 .

[28]  Van-Nam Huynh,et al.  Decision making under uncertainty with fuzzy targets , 2007, Fuzzy Optim. Decis. Mak..

[29]  Panos J. Antsaklis,et al.  Hybrid System Modeling and Autonomous Control Systems , 1992, Hybrid Systems.

[30]  Joshua M. Pearce,et al.  3-D Printing of Open Source Appropriate Technologies for Self-Directed Sustainable Development , 2010, Journal of Sustainable Development.

[31]  Alain Bernard,et al.  The evolution, challenges, and future of knowledge representation in product design systems , 2013, Comput. Aided Des..

[32]  Kenneth W. Costello,et al.  Should Utilities Compensate Customers for Service Interruptions , 2012 .

[33]  Jun Zhou,et al.  Design under Uncertainty using a Combination of Evidence Theory and a Bayesian Approach , 2008 .

[34]  Marko Čepin,et al.  Assessment of Power System Reliability , 2011 .

[35]  Loon Ching Tang,et al.  Fuzzy assessment of FMEA for engine systems , 2002, Reliab. Eng. Syst. Saf..

[36]  S. Mahadevan,et al.  A modified evidential methodology of identifying influential nodes in weighted networks , 2013 .

[37]  Songlin Chen,et al.  An evolutionary approach for product line adaptation , 2014 .

[38]  Jie Zhang,et al.  Object-oriented modeling of control system for agile manufacturing cells , 1999 .

[39]  Rahim Zamanian,et al.  Using Taguchi method for designing wedge-shaped structures for an acoustically non-reflecting test section , 2017 .

[40]  Richard J. Mayer,et al.  IDEF Family of Methods for Concurrent Engineering and Business Re-engineering Applications , 1994 .

[41]  Shih-Wen Hsiao,et al.  Fuzzy logic based decision model for product design , 1998 .

[42]  Vince Thomson,et al.  Optimal design processes under uncertainty and reciprocal dependency , 2012 .

[43]  George Q. Huang,et al.  Web-based support for collaborative product design review , 2002, Comput. Ind..

[44]  Leslie O. Morgan,et al.  Marketing/Manufacturing Trade-Offs in Product Line Management , 2001 .

[45]  Rajan Filomeno Coelho,et al.  Co-Evolutionary Optimization for Multi-Objective Design Under Uncertainty , 2013 .

[46]  U. Lindemann,et al.  UNCERTAINTY HANDLING IN INTEGRATED PRODUCT DEVELOPMENT , 2008 .

[47]  Karl T. Ulrich,et al.  Product Design and Development , 1995 .

[48]  Alberto Sillitti,et al.  Managing uncertainty in requirements: a survey in documentation-driven and agile companies , 2005, 11th IEEE International Software Metrics Symposium (METRICS'05).

[49]  Tharam S. Dillon,et al.  An intelligent fuzzy regression approach for affective product design that captures nonlinearity and fuzziness , 2011 .

[50]  D. Xiu,et al.  A new stochastic approach to transient heat conduction modeling with uncertainty , 2003 .

[51]  Eun Suk Suh,et al.  Flexible product platforms: framework and case study , 2007 .

[52]  Julio Ortega Lopera,et al.  A single front genetic algorithm for parallel multi-objective optimization in dynamic environments , 2009, Neurocomputing.

[53]  Shie Mannor,et al.  Percentile optimization in uncertain Markov decision processes with application to efficient exploration , 2007, ICML '07.

[54]  Irem Y. Tumer,et al.  Design Process Error-Proofing: Engineering Peer Review Lessons From NASA , 2004 .

[55]  David M. Anderson,et al.  Agile Product Development for Mass Customization: How to Develop and Deliver Products for Mass Customization, Niche Markets, JIT, Build-to-Order, and Flexible Manufacturing (Быстрая разработка продуктов для массовой ориентации на потребителя) , 1996 .

[56]  Jörn Mehnen,et al.  Evolutionary multi-objective design optimisation with real life uncertainty and constraints , 2009 .

[57]  Jun Zhou,et al.  Design under Uncertainty using a Combination of Evidence Theory and a Bayesian Approach , 2008 .

[58]  Ian Jenkinson,et al.  A design-decision support framework for evaluation of design options/proposals using a fuzzy-logic-based composite structure methodology , 2004 .

[59]  Lauren Basson,et al.  An integrated approach for the consideration of uncertainty in decision making supported by Life Cycle Assessment , 2007, Environ. Model. Softw..

[60]  David A. Duce,et al.  Early stage multi-level cost estimation for schematic BIM models , 2012 .

[61]  Kyung-Yong Chung,et al.  Discovery of automotive design paradigm using relevance feedback , 2013, Personal and Ubiquitous Computing.

[62]  Bharat Bhasker,et al.  Quickly locating efficient, equitable deals in automated negotiations under two-sided information uncertainty , 2011, Decis. Support Syst..

[63]  George J. Klir,et al.  A principle of uncertainty and information invariance , 1990 .

[64]  Ke Sahin,et al.  System dynamics modeling , 1980 .

[65]  Maria C. Yang,et al.  A linguistic approach to assess the dynamics of design team preference in concept selection , 2014 .

[66]  Steven L. Salzberg,et al.  Managing information for concurrent engineering: Challenges and barriers , 1990 .

[67]  Dursun Delen,et al.  Data, information and analytics as services , 2013, Decis. Support Syst..

[68]  Sofiane Achiche,et al.  Open Design and Crowdsourcing: Maturity, Methodology and Business Models , 2012 .

[69]  S. Kaplan,et al.  On The Quantitative Definition of Risk , 1981 .

[70]  Liang-Hsuan Chen,et al.  An evaluation approach to engineering design in QFD processes using fuzzy goal programming models , 2006, Eur. J. Oper. Res..

[71]  Howard Kunreuther,et al.  Is imprecise knowledge better than conflicting expertise? Evidence from insurers’ decisions in the United States , 2010 .

[72]  María Analía Rodríguez,et al.  Mid-term planning optimization model with sales contracts under demand uncertainty , 2012, Comput. Chem. Eng..

[73]  P. K. Kannan,et al.  A decision support system for product design selection: A generalized purchase modeling approach , 2006, Decis. Support Syst..

[74]  Claudia Eckert,et al.  Design process improvement : a review of current practice , 2005 .

[75]  K. Jung,et al.  Developing a Textile Design Recommendation System According to Consumers' Sensibilities , 2004 .

[76]  Lei Wang,et al.  Uncertainty quantification and propagation analysis of structures based on measurement data , 2011, Math. Comput. Model..

[77]  Ron Jeffries,et al.  Extreme Programming and Agile Software Development Methodologies , 2004, Inf. Syst. Manag..

[78]  Robert I. M. Young,et al.  Application of IDEF0, IDEF3 and UML methodologies in the creation of information models , 2000, Int. J. Comput. Integr. Manuf..

[79]  Angappa Gunasekaran,et al.  Agile manufacturing: A framework for research and development , 1999 .

[80]  Tetsuya Murai,et al.  Multiple-attribute decision making under uncertainty: the evidential reasoning approach revisited , 2006, IEEE Transactions on Systems, Man, and Cybernetics - Part A: Systems and Humans.

[81]  Forbes Gibb,et al.  Uncertainty in information seeking and retrieval: A study in an academic environment , 2011, Inf. Process. Manag..

[82]  G. Gallopin,et al.  THE ABSTRACT CONCEPT OF ENVIRONMENT , 1981 .

[83]  James D. Brown,et al.  The Data Uncertainty Engine (DUE): A software tool for assessing and simulating uncertain environmental variables , 2007, Comput. Geosci..

[84]  Suleyman Sevinc,et al.  AUTOMATION OF SIMPLIFICATION IN DISCRETE EVENT MODELLING AND SIMULATION , 1990 .

[85]  Stefan H. Thomke,et al.  The Effect of 'Front-Loading' Problem-Solving on Product Development Performance , 2000 .

[86]  Sankaran Mahadevan,et al.  Separating the contributions of variability and parameter uncertainty in probability distributions , 2013, Reliab. Eng. Syst. Saf..

[87]  D. M. Rasmuson,et al.  Uncertainties in Nuclear Probabilistic Risk Analyses , 1984 .

[88]  Shaocheng Tong,et al.  Adaptive fuzzy control of uncertain stochastic nonlinear systems with unknown dead zone using small-gain approach , 2014, Fuzzy Sets Syst..

[89]  Kwok-Leung Tsui,et al.  AN OVERVIEW OF TAGUCHI METHOD AND NEWLY DEVELOPED STATISTICAL METHODS FOR ROBUST DESIGN , 1992 .

[90]  Pierre Goovaerts,et al.  Geostatistical modelling of uncertainty in soil science , 2001 .

[91]  Tzu-An Chiang,et al.  Using DEA and GA Algorithm for Finding an Optimal Design Chain Partner Combination , 2009 .

[92]  Sean P. Kenny,et al.  Needs and Opportunities for Uncertainty- Based Multidisciplinary Design Methods for Aerospace Vehicles , 2002 .

[93]  Hyunbo Cho,et al.  Integrated framework of IDEF modelling methods for structured design of shop floor control systems , 1999, Int. J. Comput. Integr. Manuf..

[94]  Ali A. Yassine,et al.  An Introduction to Modeling and Analyzing Complex Product Development Processes Using the Design Structure Matrix (DSM) Method , 2001 .

[95]  Claudia Eckert,et al.  Design Process Improvement , 2005 .

[96]  Jérémy D'Hoinne,et al.  Could 'wait and see' be the best IPv6 strategy? , 2011, Netw. Secur..

[97]  Efstratios N. Pistikopoulos,et al.  Maintenance scheduling and process optimization under uncertainty , 2001 .

[98]  Robin S. Langley,et al.  Physical consequences of a nonparametric uncertainty model in structural dynamics , 2012 .

[99]  Jian-Bo Yang,et al.  Rule and utility based evidential reasoning approach for multiattribute decision analysis under uncertainties , 2001, Eur. J. Oper. Res..

[100]  Tyson R. Browning,et al.  Applying the design structure matrix to system decomposition and integration problems: a review and new directions , 2001, IEEE Trans. Engineering Management.

[101]  Mitsuo Nagamachi,et al.  Kansei Engineering: A new ergonomic consumer-oriented technology for product development , 1995 .

[102]  J. S. Busby,et al.  The value and limitations of using process models to describe the manufacturing organization , 1993 .

[103]  E. Antonsson,et al.  The Method of Imprecision Compared to Utility Theory for Design Selection Problems , 1993 .

[104]  Yoram Reich,et al.  Managing product quality, risk, and resources through resource quality function deployment , 2008 .

[105]  Peng He-ping,et al.  Evaluation and management procedure of measurement uncertainty in new generation geometrical product specification (GPS) , 2009 .

[106]  Francesco Ricci,et al.  A categorical model for uncertainty and cost management within the Geometrical Product Specification (GPS) framework , 2013 .

[107]  Michel van Tooren,et al.  Review of uncertainty-based multidisciplinary design optimization methods for aerospace vehicles , 2011 .

[108]  Marko Čepin,et al.  Assessment of Power System Reliability: Methods and Applications , 2011 .

[109]  Henri Prade,et al.  What are fuzzy rules and how to use them , 1996, Fuzzy Sets Syst..

[110]  Mi Zhou,et al.  Group Evidential Reasoning Approach for MADA under Fuzziness and Uncertainties , 2013, Int. J. Comput. Intell. Syst..

[111]  Hugh McManus,et al.  A framework for understanding uncertainty and its mitigation and exploitation in complex systems , 2006, IEEE Engineering Management Review.

[112]  Gerard B. M. Heuvelink,et al.  Analysing Uncertainty Propagation in GIS: Why is it not that Simple? , 2006 .

[113]  Shie Mannor,et al.  Percentile Optimization for Markov Decision Processes with Parameter Uncertainty , 2010, Oper. Res..

[114]  Shun-Peng Zhu,et al.  Risk evaluation in failure mode and effects analysis of aircraft turbine rotor blades using Dempster–Shafer evidence theory under uncertainty , 2011 .

[115]  Li-Hsing Shih,et al.  Fuzzy product line design model while considering preference uncertainty: A case study of notebook computer industry in Taiwan , 2011, Expert Syst. Appl..

[116]  E. Antonsson,et al.  Representing imprecision in engineering design: Comparing fuzzy and probability calculus , 1990 .

[117]  Sanjib Ganguly,et al.  Multi-objective planning of electrical distribution systems using dynamic programming , 2013 .

[118]  Steven C. Wheelwright,et al.  Revolutionizing Product Development: Quantum Leaps in Speed, Efficiency and Quality , 1992 .

[119]  Jianhua Dai,et al.  Approximations and uncertainty measures in incomplete information systems , 2012, Inf. Sci..

[120]  Tore Dybå,et al.  Empirical studies of agile software development: A systematic review , 2008, Inf. Softw. Technol..

[121]  Xinyu Shao,et al.  Sequential optimisation and reliability assessment for multidisciplinary design optimisation under hybrid uncertainty of randomness and fuzziness , 2013 .

[122]  Eswaran Subrahmanian,et al.  Design and planning under uncertainty: issues on problem formulation and solution , 2003, Comput. Chem. Eng..

[123]  Gila Molcho,et al.  Computer aided manufacturability analysis: Closing the knowledge gap between the designer and the manufacturer , 2008 .

[124]  Soung Hie Kim,et al.  Designing performance analysis and IDEF0 for enterprise modelling in BPR , 2002 .

[125]  Fabian Duddeck,et al.  Geometrical compatibility in structural shape optimisation for crashworthiness , 2014 .

[126]  Rob H. Bracewell,et al.  Capturing an integrated design information space with a diagram-based approach , 2013 .

[127]  Kwon-Hee Lee,et al.  Robust design for unconstrained optimization problems using the Taguchi method , 1996 .

[128]  Elsa Henriques,et al.  A method for imprecision management in complex product development , 2014 .

[129]  Améziane Aoussat,et al.  Limits of Kansei - Kansei Unlimited , 2013 .

[130]  Joaquín Bautista,et al.  A robustness information and visualization model for time and space assembly line balancing under uncertain demand , 2013 .

[131]  Marcelo Farhat de Araujo,et al.  Applying QFD to business development environment , 2013 .

[132]  H. Li,et al.  Product Design Selection Under Uncertainty and With Competitive Advantage , 2000 .

[133]  Mao-Jiun J. Wang,et al.  Hybrid fault tree analysis using fuzzy sets , 1997 .

[134]  Jon H Sims Williams,et al.  An object-oriented modeling framework for representing uncertainty in early variant design , 2003 .

[135]  P. Razi,et al.  An experimental investigation on thermo-physical properties and overall performance of MWCNT/heat transfer oil nanofluid flow inside vertical helically coiled tubes , 2012 .

[136]  Mary Drouin,et al.  Treatment of Uncertainties Associated with PRAs in Risk-Informed Decision Making (NUREG-1855) , 2009 .

[137]  M. Singh,et al.  An Evidential Reasoning Approach for Multiple-Attribute Decision Making with Uncertainty , 1994, IEEE Trans. Syst. Man Cybern. Syst..

[138]  L.-C. Chen,et al.  Constraints modelling in product design , 2002 .

[139]  J.D. Sterman,et al.  System Dynamics Modeling: Tools for Learning in a Complex World , 2001, IEEE Engineering Management Review.

[140]  Homayoon Dezfuli,et al.  Probabilistic Risk Assessment Procedures Guide for NASA Managers and Practitioners (Second Edition) , 2011 .

[141]  Randolph Kirchain,et al.  Modeling methods for managing raw material compositional uncertainty in alloy production , 2007 .

[142]  Shapour Azarm,et al.  A Customer-Based Expected Utility Metric for Product Design Selection , 2002, DAC 2002.

[143]  Jean-Yves Dantan,et al.  Geometrical product specifications - model for product life cycle , 2008, Comput. Aided Des..

[144]  Wenli Li,et al.  Collaborative production planning of supply chain under price and demand uncertainty , 2011, Eur. J. Oper. Res..