Metrics for Assessment and Management of Lean Manufacturing Implementation

This research is to introduce a new concept of auditing and implementing Lean Manufacturing by translating qualitative criteria to quantitative metrics. Therefore, quantitative formulas were developed to produce a numeric score, representing the progress of three lean manufacturing tools implementation. The tools are 5S, Kaizen, and Value Stream Mapping. The scores could then be compared to an ideal state or a standard set by industrial studies (i.e. baseline). These tools were chosen based on the researcher’s industrial experience and the gap seen in assessing the implementation of these three tools. Other metric formulas with the same approach could be derived for other tools and altered to better-fit different industrial requirements. For the provided metrics, a binary system (i.e. 1 or 0) is used to reduce auditing variations and discrepancies, producing a numeric score. These metrics were demonstrated through hypothetical and actual case studies to prove their industrial practicality. The developed 5S scoring metric was compared to a followed auditing system in a machine and tool manufacturer in Windsor, ON, Canada. The Value Stream Mapping case study was adapted from the literature while the Kaizen case was a hypothetical example to prove the metrics practicality. A score was generated by each tool metric and combined in an Overall Lean Score. These scores are more relatable to current and future states in comparison to implementation checklists and questionnaires with no solid indicators (i.e. numeric, descriptive, suggestive, etc.). The significance of this research lies in the ease to track and set goals for future progress plans compared to current states. Such plans could include upgrading to various manufacturing paradigms such as Industry 4.0 in which all information is digitized. Therefore, the lean implementation should extend from applying the lean tools to numerical values (i.e. metrics).

Name thesis:degree_name

M.A.Sc.

Level thesis:degree_level

Masters

Discipline thesis:degree_discipline

Industrial and Manufacturing Systems Engineering

Grantor

University of Windsor

Year dc:date.issued

2018

Author dc:creator

• Ghali, Mina

Advisor dc:contributor.advisor

• El Maraghy, Waguih H.

Contributors dc:contributor

• mita@uwindsor.ca

Licence

• http://creativecommons.org/licenses/by-nc-nd/4.0/

Language dc:language.iso

en_CA

Handle dc:identifier.uri

https://hdl.handle.net/20.500.14776/7809

OAI identifier oai:identifier

oai:uwindsor.scholaris.ca:20.500.14776/7809