Society of Reliability Engineering Ottawa

Toronto, Canada

Society of Reliability Engineering Ottawa

Toronto, Canada

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Samarrokhi A.,Multi Media University | Jenab K.,Society of Reliability Engineering Ottawa | Weinsier P.D.,Bowling Green State University
International Journal of Services and Operations Management | Year: 2015

The aim of this study was to examine whether or not unique resources can play a moderating role in the effects of lean production and Six Sigma on sustainable competitive advantage (SCA) and improve these effects. This was an exploratory descriptive research study and the investigation was based on a causal approach that surveyed the effects of lean and Six Sigma on sustainable competitive advantage and whether or not unique resources are able to leverage these impacts. All variables were measured by reliable and valid measures and data were analysed by bivariate correlation and multiple regression. This study showed that the effects of lean production and Six Sigma on manufacturers' sustainable competitive advantage would not be improved by applying unique resources. Although there are many studies focusing only on lean, Six Sigma, resources or sustainable competitive advantage individually, this current study revealed new guidelines that have not been mentioned previously. Copyright © 2015 Inderscience Enterprises Ltd.


Jenab K.,Society of Reliability Engineering Ottawa | Sarfaraz A.,California State University, Northridge
International Journal of Enterprise Information Systems | Year: 2013

In an ever expanding connected world, mobile connectivity is essential in both commercial and private use. Selecting the best option has become increasingly difficult due to the many factors surrounding the selection of the best cell phone service providing company. Quantitative factors such as monthly price, total cell phone minutes, and phone cost are easily comparable. However, other qualitative factors such as signal coverage, vendor reputation, and customer support are not as easily analyzed. The need to make the correct decision when qualitative factors need to be considered has caused multi-criteria decision methodologies such as Analytical Hierarchy Process (AHP) to be applied in case studies. In this paper, the authors apply Fuzzy AHP to phone survey results and compare them to the original results. The multi-criteria decision methodology TOPSIS is used to demonstrate the differences between all decision methodologies. Copyright © 2013, IGI Global.


Sarfaraz A.,California State University, Northridge | Bonk R.,California State University, Northridge | Jenab K.,Society of Reliability Engineering Ottawa
International Journal of Biomedical Engineering and Technology | Year: 2014

This study reports a method for evaluating the risk and safety associated with a Bio-Artificial Liver (BAL). The methods of making Fuzzy Analytic Hierarchy Process (FAHP) have been developed in order to deal with the uncertainty. AHP has been frequently used to quantify preference relationships and aid decision making. The use of preference relationships in decision-making processes is a standard technique. Here, the use of FAHP is proposed as an evaluation method for the selection of reactors in a type of medical device known as BAL. Six BAL-support system reactors are evaluated using five criteria: safety, scalability, cell growth environment, handling and the ability to mimic native liver function. The six different BAL bio-reactor types were evaluated by three separate stakeholders. FAHP method is used to combine the different stakeholder's evaluations and rank the BAL systems for use as a temporary liver function replacement device for patients awaiting liver transplant. © 2014 Inderscience Enterprises Ltd.


Rashidi K.,Ryerson University | Jenab K.,Society of Reliability Engineering Ottawa
International Journal of Industrial and Systems Engineering | Year: 2013

Condition-based maintenance (CBM) is a maintenance strategy that reduces equipment downtime, production loss, and maintenance cost based on changes in equipment condition (e.g., changes in vibration, changes in power usage, changes in operating performance, changes in temperatures, changes in noise levels, changes in chemical composition, increase in debris content and changes in volume of material). In this study, we present the newly developed condition monitoring model (CMM) based on Bayesian decision theory, which takes vibration signals from the equipment, and classifies them to either normal or abnormal condition. Using conditional risk function, the equipment condition can be classified to either normal or abnormal condition. The conditional risk function is calculated based on loss table and the class posterior probabilities. The developed model can efficiently avoid unnecessary maintenance and make timely actions through analysing the received vibration signals from the equipment. An illustrative example is demonstrated to present the application of the model. Also, the results derived from CMM programme coded in Visual Basic are discussed. Copyright © 2013 Inderscience Enterprises Ltd.


Sarfaraz A.,Northridge | Jenab K.,Society of Reliability Engineering Ottawa | Suwanvaraboon A.,Northridge
International Journal of Industrial and Systems Engineering | Year: 2014

Nowadays, in warranty management, the problem of decision making where the operator will obtain the spare part for the warranty assistance with minimal effects on the assembly line becomes a challenge. Based on the decision criteria (extra stock, terms, reliability, cost, and amount) and available alternatives (warehouse, cannibalisation, and purchasing), we will take into consideration the most final score of alternatives with respect to the criteria that must be taken into account. Using Delphi method, this study employs a fuzzy AHP decision making approach to solve the problem. A case study is presented to demonstrate the application of the fuzzy analytic hierarchy process (fuzzy AHP) approach. Copyright © 2014 Inderscience Enterprises Ltd.

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