- Email: [email protected]
An integrated fuzzy approach for Information Technology Planning in Collaborative Product Development
7th IFAC Conference on Manufacturing Modelling, Management, and Control International Federation of Automatic Control June 19-21, 2013. Saint Petersburg, Russia
An integrated fuzzy approach for Information Technology Planning in Collaborative Product Development Jbid Arsenyan* Gülçin Büyüközkan**
* Industrial Engineering, Bahçeşehir University, Istanbul, Turkey (Tel: +90 212 381 0855; e-mail: [email protected]). ** Industrial Engineering, Galatasaray University, Istanbul, Turkey (Tel: +90 212 227 4480; e-mail: [email protected])
Abstract: Collaborative Product Development processes are generally based on technological infrastructures and various information technologies are proposed every day to facilitate collaboration, integration, co-design and co-development processes. In this highly uncertain environment, a systematic methodology is essential to plan the Information Technology infrastructure needed to start and maintain the collaborative process. This study offers an integrated Information Technology planning methodology combining Fuzzy Quality Function Deployment, Fuzzy Axiomatic Design and Fuzzy Rule Based Systems. The methodology is tested in a Collaborative Product Development case and the outcome presents an improvement path for Information Technologies for each of the collaborative parties. Keywords: Collaborative Product Development, Information Technology, Planning, Fuzzy modeling, House of Quality, Axiomatic Design, Fuzzy Rule Based Systems
and software to facilitate collaborative design reviews and other design activities (Antaki et al., 2010).
1. INTRODUCTION Collaborative Product Development (CPD) requires the integration of various firms working together on integrated platforms or at least with compatible interfaces. Not only the product design and development phase, but also the collaboration phase of CPD requires the effective coordination and communication of collaborative parties. Collaboration may imply a mere co-design or complete partnership from the planning phase to the disposal of the product. In any case, CPD includes the interaction of two or more parties making use of technological infrastructure. The right planning of technological requirements according to the necessities of the type of alliance is therefore important in improving the CPD performance given that the use of proper technology is the most preferred factor to maintain competitive advantage (Koc and Mutu, 2006). The appropriate implementation of tools and technologies enabling CPD is necessary to assure their efficiency and effectiveness (Büyüközkan, Dereli and Baykasoğlu, 2004). Technology planning and selection is included in the phase where firms’ make decisions about setting up a development project. The right decision could engender significant competitive advantages for a company in a complex business environment (Saen, 2006). New collaboration technologies were required to overcome the inherent resistance to the flow of information encountered by distributed design teams (Antaki et al., 2010). Various studies offer new infrastructures or software to increase efficiency of CPD (Buyukozkan and Arsenyan, 2012). Research was focused on developing communication tools
978-3-902823-35-9/2013 © IFAC
Krishnan and Bhattacharya (2002) study PD technology selection under technology uncertainty. They model the decision process mathematically from proven technology and prospective technology angles and they propose parallel path and sufficient design approaches to design flexibility. Gerdsri and Kocaoglu (2003) propose an analytical approach for technology selection for PD by combining the Delphi method and a hierarchical decision making model. The model consists of technology forecasting, technology characterization, technology assessment, hierarchical modelling, technology evaluation, and formation of strategic Technology Development Envelope (TDE) steps. In an extended work, Gerdsri and Kocaoglu (2007) improve the TDE framework by incorporating AHP for the hierarchical decision making model to measure intangible criteria impact as well as tangible criteria impact. Büyüközkan et al. (2004) present a comprehensive review on tools, techniques, and technologies enabling agile manufacturing in concurrent PD. Luh et al. (2009) combine Design Structure Matrix (DSM) with Fuzzy Sets Theory into FDSM to present a dynamic planning method for PD, increasing PD efficiency and decreasing development time. Ko (2010) also employs FDSM to present a methodology that enhances PD management by organizing design activities and measuring dependency strength. Oliveira and Rozenfeld (2010) integrate technology road mapping into product portfolio management and utilize the complementary features of these two techniques to support front-end PD activities. Kumar and Midha (2001) employ the QFD approach to compare a company's requirements in CPD with different
1985
10.3182/20130619-3-RU-3018.00296
2013 IFAC MIM June 19-21, 2013. Saint Petersburg, Russia
functionalities of PDM systems, and technical specifications are then compared to a specific PDM system. Rodriguez and Al-Ashaab (2005) identify CPD supporting system characteristics and classify corresponding technological requirements. They also perform a survey in the injection mould industry, and they propose a knowledge-based CPD system architecture responding to industrial requirements. Palacio et al. (2011) present a tool to facilitate collaboration in distributed SD teams that aims to increase collaboration awareness by focusing on individuals and their activities. Recent work on technology planning includes Geum et al. (2011) who propose a generic structure of product–service integrated roadmap based on the concept and typology of technological interface. They investigate the usage, characteristics, and road mapping processes. Cho and Lee (2011) present taxonomy on technology roadmaps in service areas, and they established that there were five dominant types of standardized roadmaps which could be listed as product-focused, service-focused, product-service integration, technology-driven, and finally product-service technology roadmaps. Choi et al. (2012) develop a new approach for technology planning. They consider the technology trees, which are branching diagram representing relationships among technologies, and they propose the use of SAO (subject-action-object) structure to construct a technology tree. However, literature fails to propose a comprehensive review of CPD systems mainly because these systems including various applications, tools, and plug-ins are numerous, easily outdated by new researches and only known by a limited community. Therefore, it is this study’s aim to identify the features presented by these systems, instead of identifying the systems themselves. On the other hand, the main focus of this research is limited to Information Technologies (IT) necessitated and employed in PD, due to the extensive technological requirements in development domain. This paper attempts to combine the principles of Fuzzy Quality Function Deployment (QFD), Fuzzy Axiomatic Design (AD) and Fuzzy Rule Based Systems in order to put forward a methodology to plan and implement an IT infrastructure for CPD. 2. METHODOLOGY 2.1 Review Table 1. IT requirements IT requirements
CA1 CA2 CA3 CA4 CA5 CA6 CA7 CA8 CA9
Communication Project Management Knowledge Management Product Model Data Integration & Analysis Interoperability Security Technical support Risk Management
Initially, IT requirements in CPD and responding system features available are identified through literature review and industrial feedback. Table 1 displays the outcome of the review on requirements. Communication emerges as a principal requirement in technological planning. Arsenyan and Büyüközkan (2009) highlight Information and Communication technologies as a must to assure coordination and effective collaboration. Project Management and Knowledge Management are two essential requirements as stated in the CPD structure various studies (Büyüközkan, Dereli and Baykasoğlu 2004, Rodriguez and Al-Ashaab 2005, Arsenyan and Büyüközkan 2009). Another important requirement is the product model itself. The technological infrastructure should comprise a system that enables the representation, visualization, modification of the product model, as well as other similar activities. The Data Integration & Analysis requirement can be described as a mechanism to integrate data available on different sites from different collaborating teams and to analyze the data in the most efficient manner (Lee, et al. 2009). Interoperability requirement emerges as a natural result of collaboration in order to assure diverse systems work together. The security requirement involves data protection as well as system back-up, as mentioned in Arsenyan and Büyüközkan (2009). Accordingly, risk management appears to be another requirement in CPD infrastructure. Lastly, CPD infrastructure requires Technical Support, given that collaborative infrastructure consisting of technology products may often necessitate maintenance and repair services. On the other hand, system features cover all six groups listed by Sky and Bouchal (1999) and therefore encompass general categories available in current systems. Table 2 displays the system features reviewed in response to IT requirements. Sophistication levels for each feature is also described and symbolized by L (Low), M (Medium), and H (High). Literature shows that synchronous and asynchronous communication tools are nearly always included in any collaborative system. Synchronous communication tools assure real-time communication while temporally and spatially different communication happens by asynchronous communication tools. System integration mechanisms are also widely studied in the literature. Some propose web-based interfaces to integrate various design models while others emphasize unification of modelling schemes (Buyukozkan and Arsenyan 2012). A Project management tool is indispensable in a CPD project and it serves to control and coordinate the virtual team and their tasks (Rodriguez and AlAshaab 2005). Product visualization is another feature of CPD systems. Each application differs in the functions they are presenting. Document management tools systems aim to store electronic documents and images, which enables engineering teams to create knowledge out of the information shared throughout the CPD project. Content management tools, often mistaken for data management tools, serve to manage the workflow in collaborative environments. Described as tools to keep track of the history of a dataset (Lee et al. 2009), Data Tracking & Analysis Tool enables the collaborating teams to comprehend the data they are handling. Archiving tools are also important features where
1986
2013 IFAC MIM June 19-21, 2013. Saint Petersburg, Russia
large data is shared by distributed teams as storing, retrieving, and accessing the data are assured by archiving. It is important to be able to utilize the information created during the collaboration process. Decision support tools become necessary at this stage. Providing effective decision support by making knowledge about development activities readily available and accessible contributes to PD efforts (Ramesh and Tiwana 1999). Table 2. System features and sophistication levels System features 1
Synchronous communication tools
Sophistication levels L Only telephone services M Telephone services and IM H Teleconferencing included
2
Asynchronous communication tools
L M H
System integration mechanisms
L
3
4
Project management tool
5
Product visualization
M H L M H L M H L
6
Document management tools
M H L
7
Content management tools
M H L
8
Data tracking & analysis
M H
9
Archiving tools
10
Decision support tools
L M H
Conventional House of Quality matrix is not sufficient in describing the relationships between the CAs and ECs in some cases. Fuzzy Sets Theory (Zadeh, 1975) provides a basis to handle this vagueness. Fuzzy QFD is employed in these cases in order to translate the vagueness of the relationships and the subjectivity of the evaluator into quantifiable data. In this study, House of Quality is employed in fuzzy environment as well.
Only mailing Enhanced with discussion boards Enhanced with wikis Integration partly at file transfer level Integration by universal gateways Integration at database level Spreadsheets Software such as MS Project Project tool connected to finance tools Only visualization Visualization and mark-up Collaborative modelling Software such as SharePoint Enhanced with scanning and imaging Web based document sharing and publishing Basic system without modification Connection to project management Enhanced with logistics and finance system In-house data mining systems Data mining in integrated systems Executive information systems
M
Local archiving by individuals In-house archiving tool Integrated archiving Weighted calculations on spread sheets Decision trees
H
Scenarios and simulations
L
matrix called HoQ (Figure 1). Although it constitutes a mere tool in QFD methodology, this planning matrix is widely implemented in QFD studies. Accordingly, the first phase of the technique employs House of Quality, which can be described as a “conceptual map that provides the means of inter-functional planning and communications” (Hauser and Clausing, 1988). It seeks to gather customer needs and translate into customer attributes (CAs) in order to meet them through engineering characteristics (ECs). In this study, domains 2, 3a and 5a are not employed.
Figure 1 Main domains of House of Quality 2.3 Fuzzy Axiomatic Design After the mapping process, Fuzzy AD (Suh, 1990; Kahraman and Kulak, 2005) is employed to measure how well the system features respond to requirements. As the study includes incomplete information with subjective judgments, Fuzzy AD is preferred to conventional AD in order to operate in a fuzzy environment. With Fuzzy AD, we measure how well can the system features can respond to a specific IT requirement. 2.4 Fuzzy Rule Based Systems
2.2 Fuzzy Quality Function Deployment Then a technique is developed to map these requirements into the system features, which is based on QFD. Introduced by Akao in Japan in late 1960s (Akao, 2004), QFD can be considered as a targeting technique for planning and development, an outline of events required during development, a comprehensive development plan, a means to emphasize important relationships, and a performance enhancer for the development process (Schubert, 1989). The first phase of QFD translates the voice of the customer into corresponding engineering characteristics using a planning
These two techniques put forward a weighted ranking for the implementation importance of ECs. However, this combined methodology fails to provide a “planning technique” as it fails to capture supporting aspects that are not included in the EC set. Therefore, Fuzzy Rule Based Systems are introduced to to map the fuzzy inputs into fuzzy outputs through fuzzy inference process with IF-THEN rules. Yaqiong et al. (2011) emphasize that both QFD and FRBS are techniques employed in the planning dimension in their review on quality management of distributed manufacturing systems. Table 3 presents the rules employed in the study.
1987
2013 IFAC MIM June 19-21, 2013. Saint Petersburg, Russia
Table 3. Decision rules Rule
Weight index
IC index
Budget index
Usability index
Improvement priority
1 2 3 4 5 6 7 8 9
High Low High Medium High Medium Medium Low Low
High Low Medium High Low High Medium High Medium
Low Low Low Not high Medium Low Not low
High Not low Medium Not low Not high
High Low High Medium High Medium Medium Medium Low
3. CASE STUDY The methodology is employed in a case study. Our expert is consulted for his industrial insight during the methodology development. Afterwards, the methodology is implemented within a case study in firm ABC, our case company, where our expert is the consultant for the collaboration project. French textile company ABC, specializing in camping materials, started the new line of production of photovoltaic (PV) material that generates small amount of electricity with given enough sunlight. The company wishes to promote the material for mountaineering bags and camping bags where the users can charge their mobile phone or torch batteries while hiking or trekking. This exciting idea leads to a CPD agreement between ABC and XYZ, a multinational company that produces rucksacks and camping materials. ABC, owing the electrical know-how of the PV material, will only provide the design of the front part of the bags where the PV material is used. The rest of the bag design and the overall style will be done by XYZ. A close relationship within the CPD is expected in this specific project, which will require a good deal of communication between the two companies as well as good product visualization facilities while archiving and document management gains utmost importance. XYZ is a big company with over 100 in-house IT systems people and ready to develop most of the software required for the collaboration. The stronger side of the IT is on the product visualization. On the other hand, ABC uses SAP systems for finance and logistics but again over 40 in-house IT specialists has been filling in the applications requirements where SAP failed to satisfy, mainly in the areas of textile production. Both companies formed a task force to reshape the IT solutions to achieve the optimum solutions for CPD. The alternatives for technology supplier were In-house development, SAP or ORACLE applications. The collaborative partners have already decided which alternative to choose for each system feature. The concerns were described as follows: System integration mechanism: Integration is one of the areas that can only be done by tailor made approaches where the strongest candidates are in house IT people. Project Management tool: SAP has the financial connections, so they seem to prevail over the rest of the rivals. Product visualization tool: This has already been developed by the IT people of XYZ. It only requires enhancement. Document management tool: This cannot be done by the expertise of the existing know-how in the companies and must be handled by the professional IT companies.
Content management tool: For this case of content management In-house web people are not well organized and not as efficient as the other firms. However SAP and Oracle are limited by the product catalogues, Oracle being slightly better. Data tracking & analysis tools: SAP and Oracle has more facilities but considering the customizing workload and amount of memory space used by this application, In-house IT people score better for the tailor made solutions. Also their ability to listen to the managers and to analyze the requirements is better than the customizing consultants. So these never ending requirements will be handled better by the in-house IT specialists. Archiving tool: In-house IT People always focus on backups and versions of databases but archiving is not dealt with professionally in either of the companies. Hence at this point again SAP and Oracle Score better. Decision support tool: Falls outside the expertise of in-house development team so IT giants SAP and Oracle will be better and cheaper. Such investments will be not too long term as every 3 years these firms come up with new concept of Decision Support Tools. SAP seems to be the less expensive one out of the two. Collaborative firms decided In-house development for both synchronous and asynchronous tools. The proposed technique does not seek to perform a multicriteria decision making analysis. It rather aims to offer a roadmap for technology planning. Therefore, given that the collaborative firms have decided on the alternatives to choose for each system feature, the methodology is applied to present a guide for improvement priorities of the system features. Our expert is provided with the evaluation form. Figure 2 displays the expert evaluation and the outcome of the case study. The highlighted areas are computed values (namely normalized EC priorities and IC values, as well as the decision route), whereas white cells are the data collected from the expert. The EC priorities from the HoQ, the IC computed from current state versus target values as well as budget and usability indices for each system feature of each firm are considered together to present a decision route. There are separate decision routes for each company: each party should read its own route to observe investment priorities for the system features. The outcome of the technology planning methodology clearly suggests that no system feature holds high priority. Decision route recommend low priorities on the system features, highest being Product visualization tool for ABC and Project management tool for XYZ. This is mainly due to the fact that both firms are more or less equipped in the areas of importance, given that they hold in-house IT developers. Figure 3 displays an example of the RFBS outcome for EC1 evaluation of ABC. With the given inputs (highlighted yellow), the output of the system is low improvement priority. This linguistic variable is then defuzzified as 0.13. On the other hand, a recapitulative look on the evaluation form demonstrates that the Content management tool is the system feature with the highest priority according to expert evaluation within the Fuzzy QFD. Document management
1988
2013 IFAC MIM June 19-21, 2013. Saint Petersburg, Russia
tool, Archiving tool, and Project management tool attain a high priority as well, following the Content management tool.
FAD concludes that Project management tool and Content management tool are the weaknesses of XYZ, while the main weakness of ABC is the Product visualization tool. These results are interpreted through the IC scores. 6. CONCLUSIONS This study presented a Fuzzy QFD based methodology for the technology planning in CPD projects. Given that CPD is a highly technology centred process, it is important to correctly identify the requirements, as well as appropriately plan the implementation of the technologies. The originality of the presented work lies in two aspects: Firstly, it tackles the CPD technology requirements issue and it presents a requirement set mapped into the system features available in the technology market. Also it identified the sophistication levels of the system features, given that the systems presented by the commercial packages and research project do not respond to identical levels of requirements and therefore, they need to be differentiated. The second originality of this work derives from the methodology presented. Fuzzy QFD, FAD, and FRBS are combined in order to present a planning framework for the technology improvement decisions. Fuzzy QFD is employed in order to map requirements into system features and derive the system feature priorities. The current state of the partners is matched against the targets of the CPD project in order to measure the information content, i.e. the improvement extent. The outcome of these two methodologies, combined with the budget and usability indices, operate as inputs for the FRBS. Nine rules are developed to translate these four indices into an improvement priority, which consist the outcome of the methodology. Consequently, an improvement priority is identified for each system feature for each project partner, constituting a technology planning framework. The methodology is implemented within a case study, where only drawback is reported to be the extent of the evaluation form.
Figure 2 Expert evaluation for the case study and the outcome
The proposed methodology enables CPD practitioners to identify the IT requirements according to the specifications and the level of integration of their collaboration. It hence provides a decision path for the managers of each firm with the improvement priority on the specified system feature. This decision support tool is adjustable to the specific needs of different CPD project as the relationship matrix, the target values and the indices can easily adapt to the different levels of integration, even though the requirements and system features are constant. As a prospect work, it is considered to define metrics in order to measure the budget and usability indices. The limitation of the study lies in its evaluation process. As a future work, the authors of this paper are considering the development of a decision support system where the decision makers are presented with a user interface rather than an evaluation form.
Figure 3 Decision example for ABC regarding EC1 1989
2013 IFAC MIM June 19-21, 2013. Saint Petersburg, Russia
REFERENCES Akao Akao, Y. (2004). Quality Function Deployment: Integrating Customer Requirements Into Product Design, Productivity Press. Antaki, M., Schiffauerova, A. and Thomson, V. (2010). The Performance of Technical Information Transfer in New Product Development, Concurrent Engineering, vol. 18, pp. 291-301. Arsenyan, J. and Büyüközkan, G. (2009). Modelling Collaborative Product Development Using Axiomatic Design, 15th International Conference on Concurrent Enterprising (ICE 2009). Buyukozkan, G. and Arsenyan, J. (2012). Collaborative Product Development: A Literature Overview, Production Planning & Control, vol.23, no.1, p.47-66. Büyüközkan, G., Dereli, T. and Baykasoğlu, A. (2004). A survey on the methods and tools of concurrent new product development and agile manufacturing, Journal of Intelligent Manufacturing, vol. 15, pp. 731-751. Choi, S., Park, H., Kang, D., Lee, J.Y. and Kim, K. (2012). An SAO-based text mining approach to building a technology tree for technology planning, Expert Systems with Applications, vol. 39, no. 13, p. 11443–11455. Cho, C. and Lee, S. (2011). Taxonomy of Technology Roadmaps in Service Areas, IEEE International Technology Management Conference (ITMC). - 2011, San Jose, CA , 462 - 467. Gerdsri, N. and Kocaoglu, D.F. (2003). An analytical approach to building a technology development envelope (TDE). for roadmapping of emerging technologies: a case study of emerging electronic cooling technologies for computer servers, Management of Engineering and Technology, 2003. PICMET 03. Technology Management for Reshaping the World. Portland International Conference on, Portland, OR, 380- 389. Gerdsri, N. and Kocaoglu, D.F. (2007). Applying the Analytic Hierarchy Process (AHP). to Build a Strategic Framework for Technology Roadmapping, Journal of Mathematical and Computer Modeling, vol. 46, no. 7-8, pp. 1071-1080. Geum, Y., Lee, S., Kang, D. and Park, Y. (2011). Technology roadmapping for technology-based product– service integration: A case study, Journal of Engineering and Technology Management, vol. 28, no. 3, pp. 128146. Hauser, J.R. and Clausing, D. (1988). The House of Quality, Harvard Business Review, vol. 66, no. 3, p. 63–73. Kahraman, C. and Kulak, O. (2005). Fuzzy multi-attribute decision making using an information axiom based approach, in Fuzzy Multi-Criteria Decision Making, New York: Springer US. Ko, Y.-T. (2010). A dynamic planning method for new product development management, Journal of the Chinese Institute of Industrial Engineers, vol. 27, no. 2, pp. 103-120. Koc, T. and Mutu, Y. (2006). A Technology Planning Methodology Based on Axiomatic Design Approach,
PICMET 2006 Proceedings, Istanbul, Turkey, 14501456. Krishnan, V. and Bhattacharya, S. (2002). Technology Selection and Commitment in New Product Development: The Role of Uncertainty and Design Flexibility, Management Science, vol. 48, no. 3, p. 313– 327. Kumar, R. and Midha, P.S. (2001). A QFD based methodology for evaluating a company’s PDM requirements for collaborative product development, Industrial Management & Data Systems, vol. 101, no. 3, pp. 126-132. Lee, E.S., McDonald, D.W., Anderson, N., and TarczyHornoch, P. (2009). Incorporating collaboratory concepts into informatics in support of translational interdisciplinary biomedical research, International Journal of Medical Informatics, vol. 78, pp. 10-21. Luh, D.-B., Ko, Y.-T. and Ma, C.-H. (2009). A Dynamic Planning Approach for New Product Development, Concurrent Engineering, vol. 17, no. 1, pp. 43-59. Oliveira, M.G. and Rozenfeld, H. (2010). Integrating technology roadmapping and portfolio management at the front-end of new product development, Technological Forecasting & Social Change, vol. 77, p. 1339–1354. Palacio, R.R., Vizcaino, A., Moran, A.L. and Gonzalez, V.M. (2011). Tool to facilitate appropriate interaction in global software development, IET Software, vol. 5, no. 2, pp. 157-171. Ramesh, B. and Tiwana, A. (1999). Supporting Collaborative Process Knowledge Management in New Product Development Teams, Decision Support Systems, vol. 27, pp. 213–235. Rodriguez, K. and Al-Ashaab, A. (2005). Knowledge webbased system architecture for collaborative product development, Computers in Industry, vol. 56, pp. 125140. Saen, R.F. (2006). A decision model for technology selection in the existence of both cardinal and ordinal data, Applied Mathematics and Computation, vol. 181, p. 1600–1608. Schubert, M.A. (1989). Quality function deployment-`a comprehensive tool for planning and development, Proceedings of the IEEE 1989 National Aerospace and Electronics Conference, 1989. NAECON 1989, Dayton, OH, 1498 - 1503. Sky, R.W.E. and Buchal, R.O. (1999). Modeling and Implementing Concurrent Engineering in a Virtual Collaborative Environment, Concurrent Engineering, vol. 7, pp. 279-289. Suh, N.P. (1990). The Principles of Design, New York: Oxford University Press. Yaqiong, L., Mann, L.K. and Zhang, W. (2011). Fuzzy theory applied in quality management of distributed manufacturing system: A literature review and classification , Engineering Applications of Artificial Intelligence , vol. 24, p. 266–277. Zadeh, L.A. (1975). The concept of a linguistic variable and its applications to approximate reasoning, Information Sciences, pp. 199-249 (I); 301-357 (II).
1990
An integrated fuzzy approach for Information Technology Planning in Collaborative Product Development Jbid Arsenyan* Gülçin Büyüközkan**
* Industrial Engineering, Bahçeşehir University, Istanbul, Turkey (Tel: +90 212 381 0855; e-mail: [email protected]). ** Industrial Engineering, Galatasaray University, Istanbul, Turkey (Tel: +90 212 227 4480; e-mail: [email protected])
Abstract: Collaborative Product Development processes are generally based on technological infrastructures and various information technologies are proposed every day to facilitate collaboration, integration, co-design and co-development processes. In this highly uncertain environment, a systematic methodology is essential to plan the Information Technology infrastructure needed to start and maintain the collaborative process. This study offers an integrated Information Technology planning methodology combining Fuzzy Quality Function Deployment, Fuzzy Axiomatic Design and Fuzzy Rule Based Systems. The methodology is tested in a Collaborative Product Development case and the outcome presents an improvement path for Information Technologies for each of the collaborative parties. Keywords: Collaborative Product Development, Information Technology, Planning, Fuzzy modeling, House of Quality, Axiomatic Design, Fuzzy Rule Based Systems
and software to facilitate collaborative design reviews and other design activities (Antaki et al., 2010).
1. INTRODUCTION Collaborative Product Development (CPD) requires the integration of various firms working together on integrated platforms or at least with compatible interfaces. Not only the product design and development phase, but also the collaboration phase of CPD requires the effective coordination and communication of collaborative parties. Collaboration may imply a mere co-design or complete partnership from the planning phase to the disposal of the product. In any case, CPD includes the interaction of two or more parties making use of technological infrastructure. The right planning of technological requirements according to the necessities of the type of alliance is therefore important in improving the CPD performance given that the use of proper technology is the most preferred factor to maintain competitive advantage (Koc and Mutu, 2006). The appropriate implementation of tools and technologies enabling CPD is necessary to assure their efficiency and effectiveness (Büyüközkan, Dereli and Baykasoğlu, 2004). Technology planning and selection is included in the phase where firms’ make decisions about setting up a development project. The right decision could engender significant competitive advantages for a company in a complex business environment (Saen, 2006). New collaboration technologies were required to overcome the inherent resistance to the flow of information encountered by distributed design teams (Antaki et al., 2010). Various studies offer new infrastructures or software to increase efficiency of CPD (Buyukozkan and Arsenyan, 2012). Research was focused on developing communication tools
978-3-902823-35-9/2013 © IFAC
Krishnan and Bhattacharya (2002) study PD technology selection under technology uncertainty. They model the decision process mathematically from proven technology and prospective technology angles and they propose parallel path and sufficient design approaches to design flexibility. Gerdsri and Kocaoglu (2003) propose an analytical approach for technology selection for PD by combining the Delphi method and a hierarchical decision making model. The model consists of technology forecasting, technology characterization, technology assessment, hierarchical modelling, technology evaluation, and formation of strategic Technology Development Envelope (TDE) steps. In an extended work, Gerdsri and Kocaoglu (2007) improve the TDE framework by incorporating AHP for the hierarchical decision making model to measure intangible criteria impact as well as tangible criteria impact. Büyüközkan et al. (2004) present a comprehensive review on tools, techniques, and technologies enabling agile manufacturing in concurrent PD. Luh et al. (2009) combine Design Structure Matrix (DSM) with Fuzzy Sets Theory into FDSM to present a dynamic planning method for PD, increasing PD efficiency and decreasing development time. Ko (2010) also employs FDSM to present a methodology that enhances PD management by organizing design activities and measuring dependency strength. Oliveira and Rozenfeld (2010) integrate technology road mapping into product portfolio management and utilize the complementary features of these two techniques to support front-end PD activities. Kumar and Midha (2001) employ the QFD approach to compare a company's requirements in CPD with different
1985
10.3182/20130619-3-RU-3018.00296
2013 IFAC MIM June 19-21, 2013. Saint Petersburg, Russia
functionalities of PDM systems, and technical specifications are then compared to a specific PDM system. Rodriguez and Al-Ashaab (2005) identify CPD supporting system characteristics and classify corresponding technological requirements. They also perform a survey in the injection mould industry, and they propose a knowledge-based CPD system architecture responding to industrial requirements. Palacio et al. (2011) present a tool to facilitate collaboration in distributed SD teams that aims to increase collaboration awareness by focusing on individuals and their activities. Recent work on technology planning includes Geum et al. (2011) who propose a generic structure of product–service integrated roadmap based on the concept and typology of technological interface. They investigate the usage, characteristics, and road mapping processes. Cho and Lee (2011) present taxonomy on technology roadmaps in service areas, and they established that there were five dominant types of standardized roadmaps which could be listed as product-focused, service-focused, product-service integration, technology-driven, and finally product-service technology roadmaps. Choi et al. (2012) develop a new approach for technology planning. They consider the technology trees, which are branching diagram representing relationships among technologies, and they propose the use of SAO (subject-action-object) structure to construct a technology tree. However, literature fails to propose a comprehensive review of CPD systems mainly because these systems including various applications, tools, and plug-ins are numerous, easily outdated by new researches and only known by a limited community. Therefore, it is this study’s aim to identify the features presented by these systems, instead of identifying the systems themselves. On the other hand, the main focus of this research is limited to Information Technologies (IT) necessitated and employed in PD, due to the extensive technological requirements in development domain. This paper attempts to combine the principles of Fuzzy Quality Function Deployment (QFD), Fuzzy Axiomatic Design (AD) and Fuzzy Rule Based Systems in order to put forward a methodology to plan and implement an IT infrastructure for CPD. 2. METHODOLOGY 2.1 Review Table 1. IT requirements IT requirements
CA1 CA2 CA3 CA4 CA5 CA6 CA7 CA8 CA9
Communication Project Management Knowledge Management Product Model Data Integration & Analysis Interoperability Security Technical support Risk Management
Initially, IT requirements in CPD and responding system features available are identified through literature review and industrial feedback. Table 1 displays the outcome of the review on requirements. Communication emerges as a principal requirement in technological planning. Arsenyan and Büyüközkan (2009) highlight Information and Communication technologies as a must to assure coordination and effective collaboration. Project Management and Knowledge Management are two essential requirements as stated in the CPD structure various studies (Büyüközkan, Dereli and Baykasoğlu 2004, Rodriguez and Al-Ashaab 2005, Arsenyan and Büyüközkan 2009). Another important requirement is the product model itself. The technological infrastructure should comprise a system that enables the representation, visualization, modification of the product model, as well as other similar activities. The Data Integration & Analysis requirement can be described as a mechanism to integrate data available on different sites from different collaborating teams and to analyze the data in the most efficient manner (Lee, et al. 2009). Interoperability requirement emerges as a natural result of collaboration in order to assure diverse systems work together. The security requirement involves data protection as well as system back-up, as mentioned in Arsenyan and Büyüközkan (2009). Accordingly, risk management appears to be another requirement in CPD infrastructure. Lastly, CPD infrastructure requires Technical Support, given that collaborative infrastructure consisting of technology products may often necessitate maintenance and repair services. On the other hand, system features cover all six groups listed by Sky and Bouchal (1999) and therefore encompass general categories available in current systems. Table 2 displays the system features reviewed in response to IT requirements. Sophistication levels for each feature is also described and symbolized by L (Low), M (Medium), and H (High). Literature shows that synchronous and asynchronous communication tools are nearly always included in any collaborative system. Synchronous communication tools assure real-time communication while temporally and spatially different communication happens by asynchronous communication tools. System integration mechanisms are also widely studied in the literature. Some propose web-based interfaces to integrate various design models while others emphasize unification of modelling schemes (Buyukozkan and Arsenyan 2012). A Project management tool is indispensable in a CPD project and it serves to control and coordinate the virtual team and their tasks (Rodriguez and AlAshaab 2005). Product visualization is another feature of CPD systems. Each application differs in the functions they are presenting. Document management tools systems aim to store electronic documents and images, which enables engineering teams to create knowledge out of the information shared throughout the CPD project. Content management tools, often mistaken for data management tools, serve to manage the workflow in collaborative environments. Described as tools to keep track of the history of a dataset (Lee et al. 2009), Data Tracking & Analysis Tool enables the collaborating teams to comprehend the data they are handling. Archiving tools are also important features where
1986
2013 IFAC MIM June 19-21, 2013. Saint Petersburg, Russia
large data is shared by distributed teams as storing, retrieving, and accessing the data are assured by archiving. It is important to be able to utilize the information created during the collaboration process. Decision support tools become necessary at this stage. Providing effective decision support by making knowledge about development activities readily available and accessible contributes to PD efforts (Ramesh and Tiwana 1999). Table 2. System features and sophistication levels System features 1
Synchronous communication tools
Sophistication levels L Only telephone services M Telephone services and IM H Teleconferencing included
2
Asynchronous communication tools
L M H
System integration mechanisms
L
3
4
Project management tool
5
Product visualization
M H L M H L M H L
6
Document management tools
M H L
7
Content management tools
M H L
8
Data tracking & analysis
M H
9
Archiving tools
10
Decision support tools
L M H
Conventional House of Quality matrix is not sufficient in describing the relationships between the CAs and ECs in some cases. Fuzzy Sets Theory (Zadeh, 1975) provides a basis to handle this vagueness. Fuzzy QFD is employed in these cases in order to translate the vagueness of the relationships and the subjectivity of the evaluator into quantifiable data. In this study, House of Quality is employed in fuzzy environment as well.
Only mailing Enhanced with discussion boards Enhanced with wikis Integration partly at file transfer level Integration by universal gateways Integration at database level Spreadsheets Software such as MS Project Project tool connected to finance tools Only visualization Visualization and mark-up Collaborative modelling Software such as SharePoint Enhanced with scanning and imaging Web based document sharing and publishing Basic system without modification Connection to project management Enhanced with logistics and finance system In-house data mining systems Data mining in integrated systems Executive information systems
M
Local archiving by individuals In-house archiving tool Integrated archiving Weighted calculations on spread sheets Decision trees
H
Scenarios and simulations
L
matrix called HoQ (Figure 1). Although it constitutes a mere tool in QFD methodology, this planning matrix is widely implemented in QFD studies. Accordingly, the first phase of the technique employs House of Quality, which can be described as a “conceptual map that provides the means of inter-functional planning and communications” (Hauser and Clausing, 1988). It seeks to gather customer needs and translate into customer attributes (CAs) in order to meet them through engineering characteristics (ECs). In this study, domains 2, 3a and 5a are not employed.
Figure 1 Main domains of House of Quality 2.3 Fuzzy Axiomatic Design After the mapping process, Fuzzy AD (Suh, 1990; Kahraman and Kulak, 2005) is employed to measure how well the system features respond to requirements. As the study includes incomplete information with subjective judgments, Fuzzy AD is preferred to conventional AD in order to operate in a fuzzy environment. With Fuzzy AD, we measure how well can the system features can respond to a specific IT requirement. 2.4 Fuzzy Rule Based Systems
2.2 Fuzzy Quality Function Deployment Then a technique is developed to map these requirements into the system features, which is based on QFD. Introduced by Akao in Japan in late 1960s (Akao, 2004), QFD can be considered as a targeting technique for planning and development, an outline of events required during development, a comprehensive development plan, a means to emphasize important relationships, and a performance enhancer for the development process (Schubert, 1989). The first phase of QFD translates the voice of the customer into corresponding engineering characteristics using a planning
These two techniques put forward a weighted ranking for the implementation importance of ECs. However, this combined methodology fails to provide a “planning technique” as it fails to capture supporting aspects that are not included in the EC set. Therefore, Fuzzy Rule Based Systems are introduced to to map the fuzzy inputs into fuzzy outputs through fuzzy inference process with IF-THEN rules. Yaqiong et al. (2011) emphasize that both QFD and FRBS are techniques employed in the planning dimension in their review on quality management of distributed manufacturing systems. Table 3 presents the rules employed in the study.
1987
2013 IFAC MIM June 19-21, 2013. Saint Petersburg, Russia
Table 3. Decision rules Rule
Weight index
IC index
Budget index
Usability index
Improvement priority
1 2 3 4 5 6 7 8 9
High Low High Medium High Medium Medium Low Low
High Low Medium High Low High Medium High Medium
Low Low Low Not high Medium Low Not low
High Not low Medium Not low Not high
High Low High Medium High Medium Medium Medium Low
3. CASE STUDY The methodology is employed in a case study. Our expert is consulted for his industrial insight during the methodology development. Afterwards, the methodology is implemented within a case study in firm ABC, our case company, where our expert is the consultant for the collaboration project. French textile company ABC, specializing in camping materials, started the new line of production of photovoltaic (PV) material that generates small amount of electricity with given enough sunlight. The company wishes to promote the material for mountaineering bags and camping bags where the users can charge their mobile phone or torch batteries while hiking or trekking. This exciting idea leads to a CPD agreement between ABC and XYZ, a multinational company that produces rucksacks and camping materials. ABC, owing the electrical know-how of the PV material, will only provide the design of the front part of the bags where the PV material is used. The rest of the bag design and the overall style will be done by XYZ. A close relationship within the CPD is expected in this specific project, which will require a good deal of communication between the two companies as well as good product visualization facilities while archiving and document management gains utmost importance. XYZ is a big company with over 100 in-house IT systems people and ready to develop most of the software required for the collaboration. The stronger side of the IT is on the product visualization. On the other hand, ABC uses SAP systems for finance and logistics but again over 40 in-house IT specialists has been filling in the applications requirements where SAP failed to satisfy, mainly in the areas of textile production. Both companies formed a task force to reshape the IT solutions to achieve the optimum solutions for CPD. The alternatives for technology supplier were In-house development, SAP or ORACLE applications. The collaborative partners have already decided which alternative to choose for each system feature. The concerns were described as follows: System integration mechanism: Integration is one of the areas that can only be done by tailor made approaches where the strongest candidates are in house IT people. Project Management tool: SAP has the financial connections, so they seem to prevail over the rest of the rivals. Product visualization tool: This has already been developed by the IT people of XYZ. It only requires enhancement. Document management tool: This cannot be done by the expertise of the existing know-how in the companies and must be handled by the professional IT companies.
Content management tool: For this case of content management In-house web people are not well organized and not as efficient as the other firms. However SAP and Oracle are limited by the product catalogues, Oracle being slightly better. Data tracking & analysis tools: SAP and Oracle has more facilities but considering the customizing workload and amount of memory space used by this application, In-house IT people score better for the tailor made solutions. Also their ability to listen to the managers and to analyze the requirements is better than the customizing consultants. So these never ending requirements will be handled better by the in-house IT specialists. Archiving tool: In-house IT People always focus on backups and versions of databases but archiving is not dealt with professionally in either of the companies. Hence at this point again SAP and Oracle Score better. Decision support tool: Falls outside the expertise of in-house development team so IT giants SAP and Oracle will be better and cheaper. Such investments will be not too long term as every 3 years these firms come up with new concept of Decision Support Tools. SAP seems to be the less expensive one out of the two. Collaborative firms decided In-house development for both synchronous and asynchronous tools. The proposed technique does not seek to perform a multicriteria decision making analysis. It rather aims to offer a roadmap for technology planning. Therefore, given that the collaborative firms have decided on the alternatives to choose for each system feature, the methodology is applied to present a guide for improvement priorities of the system features. Our expert is provided with the evaluation form. Figure 2 displays the expert evaluation and the outcome of the case study. The highlighted areas are computed values (namely normalized EC priorities and IC values, as well as the decision route), whereas white cells are the data collected from the expert. The EC priorities from the HoQ, the IC computed from current state versus target values as well as budget and usability indices for each system feature of each firm are considered together to present a decision route. There are separate decision routes for each company: each party should read its own route to observe investment priorities for the system features. The outcome of the technology planning methodology clearly suggests that no system feature holds high priority. Decision route recommend low priorities on the system features, highest being Product visualization tool for ABC and Project management tool for XYZ. This is mainly due to the fact that both firms are more or less equipped in the areas of importance, given that they hold in-house IT developers. Figure 3 displays an example of the RFBS outcome for EC1 evaluation of ABC. With the given inputs (highlighted yellow), the output of the system is low improvement priority. This linguistic variable is then defuzzified as 0.13. On the other hand, a recapitulative look on the evaluation form demonstrates that the Content management tool is the system feature with the highest priority according to expert evaluation within the Fuzzy QFD. Document management
1988
2013 IFAC MIM June 19-21, 2013. Saint Petersburg, Russia
tool, Archiving tool, and Project management tool attain a high priority as well, following the Content management tool.
FAD concludes that Project management tool and Content management tool are the weaknesses of XYZ, while the main weakness of ABC is the Product visualization tool. These results are interpreted through the IC scores. 6. CONCLUSIONS This study presented a Fuzzy QFD based methodology for the technology planning in CPD projects. Given that CPD is a highly technology centred process, it is important to correctly identify the requirements, as well as appropriately plan the implementation of the technologies. The originality of the presented work lies in two aspects: Firstly, it tackles the CPD technology requirements issue and it presents a requirement set mapped into the system features available in the technology market. Also it identified the sophistication levels of the system features, given that the systems presented by the commercial packages and research project do not respond to identical levels of requirements and therefore, they need to be differentiated. The second originality of this work derives from the methodology presented. Fuzzy QFD, FAD, and FRBS are combined in order to present a planning framework for the technology improvement decisions. Fuzzy QFD is employed in order to map requirements into system features and derive the system feature priorities. The current state of the partners is matched against the targets of the CPD project in order to measure the information content, i.e. the improvement extent. The outcome of these two methodologies, combined with the budget and usability indices, operate as inputs for the FRBS. Nine rules are developed to translate these four indices into an improvement priority, which consist the outcome of the methodology. Consequently, an improvement priority is identified for each system feature for each project partner, constituting a technology planning framework. The methodology is implemented within a case study, where only drawback is reported to be the extent of the evaluation form.
Figure 2 Expert evaluation for the case study and the outcome
The proposed methodology enables CPD practitioners to identify the IT requirements according to the specifications and the level of integration of their collaboration. It hence provides a decision path for the managers of each firm with the improvement priority on the specified system feature. This decision support tool is adjustable to the specific needs of different CPD project as the relationship matrix, the target values and the indices can easily adapt to the different levels of integration, even though the requirements and system features are constant. As a prospect work, it is considered to define metrics in order to measure the budget and usability indices. The limitation of the study lies in its evaluation process. As a future work, the authors of this paper are considering the development of a decision support system where the decision makers are presented with a user interface rather than an evaluation form.
Figure 3 Decision example for ABC regarding EC1 1989
2013 IFAC MIM June 19-21, 2013. Saint Petersburg, Russia
REFERENCES Akao Akao, Y. (2004). Quality Function Deployment: Integrating Customer Requirements Into Product Design, Productivity Press. Antaki, M., Schiffauerova, A. and Thomson, V. (2010). The Performance of Technical Information Transfer in New Product Development, Concurrent Engineering, vol. 18, pp. 291-301. Arsenyan, J. and Büyüközkan, G. (2009). Modelling Collaborative Product Development Using Axiomatic Design, 15th International Conference on Concurrent Enterprising (ICE 2009). Buyukozkan, G. and Arsenyan, J. (2012). Collaborative Product Development: A Literature Overview, Production Planning & Control, vol.23, no.1, p.47-66. Büyüközkan, G., Dereli, T. and Baykasoğlu, A. (2004). A survey on the methods and tools of concurrent new product development and agile manufacturing, Journal of Intelligent Manufacturing, vol. 15, pp. 731-751. Choi, S., Park, H., Kang, D., Lee, J.Y. and Kim, K. (2012). An SAO-based text mining approach to building a technology tree for technology planning, Expert Systems with Applications, vol. 39, no. 13, p. 11443–11455. Cho, C. and Lee, S. (2011). Taxonomy of Technology Roadmaps in Service Areas, IEEE International Technology Management Conference (ITMC). - 2011, San Jose, CA , 462 - 467. Gerdsri, N. and Kocaoglu, D.F. (2003). An analytical approach to building a technology development envelope (TDE). for roadmapping of emerging technologies: a case study of emerging electronic cooling technologies for computer servers, Management of Engineering and Technology, 2003. PICMET 03. Technology Management for Reshaping the World. Portland International Conference on, Portland, OR, 380- 389. Gerdsri, N. and Kocaoglu, D.F. (2007). Applying the Analytic Hierarchy Process (AHP). to Build a Strategic Framework for Technology Roadmapping, Journal of Mathematical and Computer Modeling, vol. 46, no. 7-8, pp. 1071-1080. Geum, Y., Lee, S., Kang, D. and Park, Y. (2011). Technology roadmapping for technology-based product– service integration: A case study, Journal of Engineering and Technology Management, vol. 28, no. 3, pp. 128146. Hauser, J.R. and Clausing, D. (1988). The House of Quality, Harvard Business Review, vol. 66, no. 3, p. 63–73. Kahraman, C. and Kulak, O. (2005). Fuzzy multi-attribute decision making using an information axiom based approach, in Fuzzy Multi-Criteria Decision Making, New York: Springer US. Ko, Y.-T. (2010). A dynamic planning method for new product development management, Journal of the Chinese Institute of Industrial Engineers, vol. 27, no. 2, pp. 103-120. Koc, T. and Mutu, Y. (2006). A Technology Planning Methodology Based on Axiomatic Design Approach,
PICMET 2006 Proceedings, Istanbul, Turkey, 14501456. Krishnan, V. and Bhattacharya, S. (2002). Technology Selection and Commitment in New Product Development: The Role of Uncertainty and Design Flexibility, Management Science, vol. 48, no. 3, p. 313– 327. Kumar, R. and Midha, P.S. (2001). A QFD based methodology for evaluating a company’s PDM requirements for collaborative product development, Industrial Management & Data Systems, vol. 101, no. 3, pp. 126-132. Lee, E.S., McDonald, D.W., Anderson, N., and TarczyHornoch, P. (2009). Incorporating collaboratory concepts into informatics in support of translational interdisciplinary biomedical research, International Journal of Medical Informatics, vol. 78, pp. 10-21. Luh, D.-B., Ko, Y.-T. and Ma, C.-H. (2009). A Dynamic Planning Approach for New Product Development, Concurrent Engineering, vol. 17, no. 1, pp. 43-59. Oliveira, M.G. and Rozenfeld, H. (2010). Integrating technology roadmapping and portfolio management at the front-end of new product development, Technological Forecasting & Social Change, vol. 77, p. 1339–1354. Palacio, R.R., Vizcaino, A., Moran, A.L. and Gonzalez, V.M. (2011). Tool to facilitate appropriate interaction in global software development, IET Software, vol. 5, no. 2, pp. 157-171. Ramesh, B. and Tiwana, A. (1999). Supporting Collaborative Process Knowledge Management in New Product Development Teams, Decision Support Systems, vol. 27, pp. 213–235. Rodriguez, K. and Al-Ashaab, A. (2005). Knowledge webbased system architecture for collaborative product development, Computers in Industry, vol. 56, pp. 125140. Saen, R.F. (2006). A decision model for technology selection in the existence of both cardinal and ordinal data, Applied Mathematics and Computation, vol. 181, p. 1600–1608. Schubert, M.A. (1989). Quality function deployment-`a comprehensive tool for planning and development, Proceedings of the IEEE 1989 National Aerospace and Electronics Conference, 1989. NAECON 1989, Dayton, OH, 1498 - 1503. Sky, R.W.E. and Buchal, R.O. (1999). Modeling and Implementing Concurrent Engineering in a Virtual Collaborative Environment, Concurrent Engineering, vol. 7, pp. 279-289. Suh, N.P. (1990). The Principles of Design, New York: Oxford University Press. Yaqiong, L., Mann, L.K. and Zhang, W. (2011). Fuzzy theory applied in quality management of distributed manufacturing system: A literature review and classification , Engineering Applications of Artificial Intelligence , vol. 24, p. 266–277. Zadeh, L.A. (1975). The concept of a linguistic variable and its applications to approximate reasoning, Information Sciences, pp. 199-249 (I); 301-357 (II).
1990