Forthcoming articles


International Journal of Experimental Design and Process Optimisation


These articles have been peer-reviewed and accepted for publication in IJEDPO, but are pending final changes, are not yet published and may not appear here in their final order of publication until they are assigned to issues. Therefore, the content conforms to our standards but the presentation (e.g. typesetting and proof-reading) is not necessarily up to the Inderscience standard. Additionally, titles, authors, abstracts and keywords may change before publication. Articles will not be published until the final proofs are validated by their authors.


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International Journal of Experimental Design and Process Optimisation (2 papers in press)


Regular Issues


  • Development of Performance Loss Functions for Healthcare Applications   Order a copy of this article
    by Kathryn Pegues 
    Abstract: Relatively recent advances in both medical knowledge and increased technological capability to measure changes within the human body have made the role of a healthcare provider increasingly difficult. Doctors are expected to digest excessive amounts of data and, from that data, develop actionable recommendations in a timely fashion. This global expectation of healthcare providers creates a demand for increased involvement of other specialties within the scientific community in the development of better methodologies for transforming data into information and then using the resultant information to develop optimal treatment plans. The Precision Medicine Initiative outlines a goal of tailoring medical care for the individual patient. For this effort to be successful, it is incumbent upon research teams to think critically about the problem at hand, determine what aspect of patient treatment their field could provide assistance in improving, and start an open dialogue with the medical community. This paper seeks to establish an informative exchange as to how quality engineering methodologies can be applied to treatment protocol selection by examining how to adapt the quality loss function for use within the healthcare domain. In support of a larger effort to develop improved metrics for health assessments and patients physical performance this article develops the concept of reference interval-based performance functions.
    Keywords: Quality; healthcare; loss functions; performance; target ranges.

  • The development of a customer-centred, response surface methodology-based robust parameter design optimization model under a moderately skewed production process   Order a copy of this article
    by Hsin-Li Chan, Akin Ozdemir 
    Abstract: The philosophy of Quality by Design (QbD) has been developed to facilitate a proactive improvement by incorporating quality into production processes. Robust parameter design (RPD), one of the most effective QbD methods, identifies optimum operating conditions that achieve a target value with minimum variance. However, the vast majority of RPD models have been developed with a manufacturers point of view based on the assumption that the process is normally distributed. This paper contributes to the current body of knowledge by reconsidering traditional RPD concepts in two ways. First, it is known that quality should be viewed from the customer point of view. Final products are often subjected to screening inspection and only conforming products are distributed to the customer, while rejected products are scrapped or reworked. This inspection of the products results in a truncated distribution. Second, real-world process distributions for smaller-the better and larger-the-better quality characteristics are often skewed. Accordingly, this paper develops response surface methodology-based RPD models by introducing a skew normal distribution and integrating the customers perceived truncated statistics into RPD. Comparative studies are also presented. Finally, numerical examples show that the proposed optimization schemes are superior over the traditional counterparts.
    Keywords: quality; robust parameter design; truncation; skew normal distribution; nonlinear programming.