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Amir Abolhassani
Researcher at Ford Motor Company
Publications - 12
Citations - 170
Amir Abolhassani is an academic researcher from Ford Motor Company. The author has contributed to research in topics: Productivity & Lean manufacturing. The author has an hindex of 5, co-authored 10 publications receiving 121 citations. Previous affiliations of Amir Abolhassani include West Virginia University.
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Journal ArticleDOI
Lean and US manufacturing industry: popularity of practices and implementation barriers
TL;DR: The most beneficial and least difficult lean strategies, their implementation level, and the real challenges for implementing lean were also identified to help both lean practitioner and non-practitioner for the lean journey as discussed by the authors.
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Specification of energy assessment methodologies to satisfy ISO 50001 energy management standard
Harish Kanneganti,Bhaskaran Gopalakrishnan,Ed Crowe,Omar Ahmed Al-Shebeeb,Omar Ahmed Al-Shebeeb,Tarun Yelamanchi,Ashish D. Nimbarte,Kenneth R. Currie,Amir Abolhassani +8 more
TL;DR: In this paper, the authors developed an energy assessment methodology and reporting format tailored to the needs of ISO 50001, which integrates the energy reduction aspect of an assessment with the requirements of Sections 4.4.3 (Energy Review) to 4.6 (Objectives, targets, and action plans) in ISO 5001, thus enabling facilities to reduce the time and other resources required for facilitating the implementation of ISO50001.
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Empirical analysis of productivity enhancement strategies in the North American automotive industry
TL;DR: In this article, robust and hybrid models of the most popular productivity measurement in the automotive industry, hours per vehicle (HPV), are developed. And a hybrid method, the combination of multiple M-estimators and a lasso, is developed and was shown to be the best method to determine a robust regression model to estimate HPV.
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Productivity enhancement strategies in North American automotive industry
TL;DR: Depending on the car class, the vehicle variety, model types, annual working days, car assembly utilisation and launching a new model penalise HPV; however, annual production volume, flexible manufacturing and year of production improve HPV.
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Manufacturing Process Monitoring With Nonparametric Change-Point Detection in Automotive Industry
Shenghan Guo,Weihong Guo,Amir Abolhassani,Rajeev Kalamdani,Saumuy Puchala,Annette Januszczak,Chandra Jalluri +6 more
TL;DR: A systematic approach for detecting process changes retrospectively in complex, nonstationary data is developed and it is shown that LASSO and thresholded-LASSO outperform WBS when the shift size is small, but WBS produces a smaller false alarm rate and handles the clustering of changes better than LassO or thresholded LASSo.