Technology selection in the absence of standardised materials and processes: a survey in the UK composite materials supply chain

Abstract Composite materials is an industry where technology selection has major consequences as there is not a standard manufacturing process, nor are there standardised materials with defined or proscribed properties for companies to select as multiple solutions are technically viable. This research aims to identify key factors for manufacturing technology selection in the UK composite materials supply chain. Literature review and managers’ opinions were used to identify 18 factors affecting manufacturing technology selection. This was followed by a survey comprising the multi-tier supply chain of the composite materials industry. The results of the survey show ‘on time deliveries/service level to customers’, ‘improve quality’ and ‘reduce cycle time’ received the highest average ratings. In this study a correlation analysis was performed to identify the underlying dependencies between the factors investigated. The identification and use of underlying dependencies rather than highest average provided a more comprehensive picture of the factors that affect technology selection in the composite materials industry. For this study, experts in composite materials were asked to comment on the findings of the survey and their value to the industry. The results presented may assist companies in the composite materials industry with technology selection decision-making processes.

[1]  Bimal Nepal,et al.  On supply chain competitiveness of Indian automotive component manufacturing industry , 2013 .

[2]  Yufeng Zhang,et al.  Exploring how complex solution-based capabilities (CSC) are developed and integrated in engineering companies , 2016 .

[3]  Georg von Krogh,et al.  Is open innovation a field of study or a communication barrier to theory development?: A commentary , 2011 .

[4]  Paul R. Kleindorfer,et al.  Integrating manufacturing strategy and technology choice , 1990 .

[5]  Helen Boulton Action research: a methodology , 2011 .

[6]  Abraham Mendoza,et al.  Analytical models for supplier selection and order quantity allocation , 2012 .

[7]  Ashutosh Sarkar,et al.  Evaluation of supplier capability and performance: A method for supply base reduction , 2006 .

[8]  Keith Ridgway,et al.  QFD in new production technology evaluation , 2000 .

[9]  Chun-Wei R. Lin,et al.  A fuzzy strategic alliance selection framework for supply chain partnering under limited evaluation resources , 2004, Comput. Ind..

[10]  Eve D. Rosenzweig,et al.  The influence of an integration strategy on competitive capabilities and business performance: An exploratory study of consumer products manufacturers , 2003 .

[11]  David J. Barnes,et al.  Formulating partner selection criteria for agile supply chains: A Dempster-Shafer belief acceptability optimisation approach , 2010 .

[12]  J. Gill,et al.  Research Methods For Managers , 1991 .

[13]  D. Lambert,et al.  Issues in Supply Chain Management , 2000 .

[14]  P. Parthiban,et al.  Vendor selection problem: a multi-criteria approach based on strategic decisions , 2013 .

[15]  A. C. Lyons *,et al.  Prototyping an information system's requirements architecture for customer-driven, supply-chain operations , 2005 .

[16]  Timothy M. Young,et al.  Predicting Key Reliability Response with Limited Response Data , 2014 .

[17]  Sami Farooq,et al.  An action research methodology for manufacturing technology selection: a supply chain perspective , 2015 .

[18]  Hossein Sharifi,et al.  A methodology for achieving agility in manufacturing organisations : An introduction , 1999 .

[19]  David J. Barnes,et al.  Partner selection in agile supply chains: a fuzzy intelligent approach , 2014 .

[20]  Xiaojun Wang,et al.  A two-stage Fuzzy-AHP model for risk assessment of implementing green initiatives in the fashion supply chain , 2012 .

[21]  W. B. Lee,et al.  Design of a case based intelligent supplier relationship management system - the integration of supplier rating system and product coding system , 2003, Expert Syst. Appl..

[22]  L. D. Boer,et al.  A review of methods supporting supplier selection , 2001 .

[23]  Detelin S. Elenkov,et al.  Organizational capacity for change and environmental performance: an empirical assessment of Bulgarian firms , 2005 .

[24]  Jonathan D. Linton,et al.  Is open innovation a field of study or a communication barrier to theory development , 2010 .

[25]  Andrew C. Lyons,et al.  Investigating the implications of extending synchronized sequencing in automotive supply chains: the case of suppliers in the European automotive sector , 2008 .

[26]  Bo Chen,et al.  Relationships among circumstance pressure, green technology selection and firm performance , 2015 .

[27]  John W. Creswell,et al.  Research Design: Qualitative, Quantitative, and Mixed Methods Approaches , 2010 .

[28]  Peng Wang,et al.  A hybrid method using experiment design and grey relational analysis for multiple criteria decision making problems , 2013, Knowl. Based Syst..

[29]  Felix T.S. Chan,et al.  Evaluation methodologies for technology selection , 2000 .

[30]  Mark Rowling,et al.  THE SELECTION PROCESS , 2001 .

[31]  Benjamin T. Hazen,et al.  Adoption of cloud computing technologies in supply chains: An organizational information processing theory approach , 2012 .

[32]  Christopher O'Brien,et al.  A technology selection framework for integrating manufacturing within a supply chain , 2012 .

[33]  W. B. Lee,et al.  An intelligent supplier management tool for benchmarking suppliers in outsource manufacturing , 2002, Expert Syst. Appl..

[34]  Stephan M. Wagner,et al.  The link between supply chain fit and financial performance of the firm , 2012 .

[35]  David J. Barnes,et al.  A literature review of decision-making models and approaches for partner selection in agile supply chains , 2011 .

[36]  Andrew Taylor,et al.  Integrating new technology in established organizations: A mapping of integration mechanisms , 2010 .

[37]  Yu-Ying Huang,et al.  How to achieve leagility: A case study of a personal computer original equipment manufacturer in Taiwan , 2010 .

[38]  Chih-Hsuan Wang,et al.  Using quality function deployment for collaborative product design and optimal selection of module mix , 2012, Comput. Ind. Eng..

[39]  Ralf W. Seifert,et al.  Interrelating operational and financial performance measurements in inventory control , 2010, Eur. J. Oper. Res..

[40]  Weijun Xia,et al.  Supplier selection with multiple criteria in volume discount environments , 2007 .

[41]  J. Lin,et al.  Determinants of manufacturers' selection of distributors , 2008 .

[42]  Chong Wu,et al.  A dynamic feedback model for partner selection in agile supply chains , 2012 .

[43]  Fredrik Elgh,et al.  Decision support in the quotation process of engineered-to-order products , 2012, Adv. Eng. Informatics.

[44]  David J. Barnes,et al.  Supplier selection in agile supply chains: An information-processing model and an illustration , 2009 .

[45]  H. Taşkin,et al.  Supplier selection: an expert system approach , 2007 .

[46]  James T. Lin,et al.  3PL selection criteria in integrated circuit manufacturing industry in Taiwan , 2016 .