A Qualitative Performance Measurement Approach to New Product Development

Tom Page*
Periodicity:September - November'2009
DOI : https://doi.org/10.26634/jmgt.4.2.1062


The main application of fuzzy logic in manufacturing has been through type-1 fuzzy sets leaving type-2 fuzzy sets behind. It is felt that type-2 fuzzy sets have the potential of being exploited on a similar scale to type-1 fuzzy sets, because of the additional advantages of containing more information about uncertainty.

The essence of type-2 is in capturing uncertainty in rule-bases by making the degrees of membership to fuzzy sets, fuzzy themselves. Type-2 fuzzy sets are used when (1) linguistic labels of fuzzy sets are uncertain, (2) there is more then one expert, (3) input data into the fuzzy model is uncertain, and (4) training data is uncertain for adaptive modelling. In this research (1) and (2) lead to the use of type-2 fuzzy sets for evaluating a New Product Introduction process. In particular the New Product Introduction Process is explored and documented in a high technology goods manufacturer. The work uses soft systems methodology, cause and effect diagrams, and process maps to document the use of and sharing of information and also to identify the causes of extended time to market.

Initially qualitative data is used to capture model structure by identifying linguistic variables and relationships between them. It is found that the variables can be arranged in a hierarchy to effectively reduce the potential number of rules. A questionnaire is prepared in order to capture further data to identify fuzzy set parameters and lead to type-2 fuzzy sets.  The remainder of the paper finds some initial results and further illuminates the methodology of using type-2 fuzzy sets.


Qualitative Performance Measurement, New Product Development.

How to Cite this Article?

Tom Page (2009). A Qualitative Performance Measurement Approach to New Product Development. i-manager’s Journal on Management, 4(2), 63-67. https://doi.org/10.26634/jmgt.4.2.1062


[1]. Maskell, B. and Baggaley, B. (2003), Practical Lean Accounting, Productivity Press.
[2]. Bicheno, J. (1998), The Lean Toolbox, 2 Ed., Picsie Books.
[4]. Nojiri, H. (1982), A model of the executive's decision processes in new product development, Fuzzy sets and systems 7, 227-241.
[5]. Jahan-Shahi, H., Shayan, E. and Masood, S.H. (2001), Multi-valued fuzzy sets in cost / time estimation of flat plate processing, International Journal of Advanced Manufacturing Technology 17, 751-759.
[6]. Yager, R. R. (2003), Noble reinforcement in disjunctive aggregation operators, IEEE Transactions on Fuzzy Systems, Vol. 11. No. 6,pp.754-767.
[7]. Last M. and Kandel, A. (2002), Perception-based analysis of engineering experiments in the semiconductor industry, International Journal of Image and Graphics, Vol. 2. No. 1,pp.107-126.
[8]. Koliza, V., Pearce, D., Khoudian P. and Page, T. (2003), Formulation of a calculation for identifying actual and potential costs caused by delays in the new product introduction process, Proceedings of the 19th NCMR and st 1 ICMR, University of Strathclyde, September, 229-233.

Purchase Instant Access

Single Article

North Americas,UK,
Middle East,Europe
India Rest of world
Pdf 35 35 200 20
Online 35 35 200 15
Pdf & Online 35 35 400 25

If you have access to this article please login to view the article or kindly login to purchase the article
Options for accessing this content:
  • If you would like institutional access to this content, please recommend the title to your librarian.
    Library Recommendation Form
  • If you already have i-manager's user account: Login above and proceed to purchase the article.
  • New Users: Please register, then proceed to purchase the article.