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SRE Ottawa Blog
articles, stories, past newsletters from the community

  • Arun Gowtham
  • Dec 1, 2021
  • 2 min read

For seminar event#336, SRE Ottawa hosted Shamir Doshi, Lean Manufacturing Engineer, Gastops Inc., Ottawa, ON for his presentation titled "Avoiding failure in Lean deployment: proactive management methods to improve productivity, quality, and reliability".


Shamir delivered an interesting presentation that delved into the crevices of Project Management to explain the impact a good proactive management practice can have on avoiding failures of products. This was a refreshing take on the topic that most of the teams neglect to consider, especially in large organizations with multi-level structure. How do you manage people with different mental maps approaching problems in their unique way? Are you giving the correct incentive for your team members? How has the quality or reliability of your products fared due to this misalignment in your team's work? All organizations face this type of challenge in some ways and the presenter shared methods on how to approach it.


Primary step is to take a proactive management role by the Team Leader and utilize the objective tools available to create a streamlined workflow. Once a structure is established, encourage the team members to follow the path and iterate improvements. There is a real potential in tapping into the knowledge of the team through effective brainstorming sessions. This can result in improved Quality, Reliability, and Safety. Underlying all the above solutions is a "proactive management mindset".



Shamir Doshi graciously shared the below reading materials for our community.


Video Clips from the discussion:

Further Reading Resources:

  1. NUMMI - How one car plant saved U.S. car industry

  2. The Puritan Gift: Reclaiming the American Dream Amidst Global Financial Chaos, Mar 17 2009 by Ken Hopper and Will Hopper

  3. Standardized Work with TWI: Eliminating Human Errors in Production and Service Processes Paperback Released: April 4 2016 by Bartosz Misiurek (Author)

  4. The Lean Farm: How to Minimize Waste, Increase Efficiency, and Maximize Value and Profits with Less Work Released: Sept. 16 2015 by Ben Hartman

  5. The Complete Lean Enterprise: Value Stream Mapping for Office and Services, Second Edition Paperback, Dec 10 2015 by Beau Keyte, Drew A. Locher

  6. The Perfect Engine: Driving Manufacturing Breakthroughs with the Globa Paperback, May 7 2011 by Patricia E. Moody, Anand Sharma

  7. Taiichi Ohnos Workplace Management: Special 100th Birthday Edition by Taiichi Ohno | Dec 11 2012

  8. Toyota Production System: Beyond Large-Scale Production by Taiichi Ohno and Norman Bodek | Dec 17 2019

  9. The Toyota Way, Second Edition: 14 Management Principles from the World's Greatest Manufacturer by Jeffrey Liker | Dec 1 2020

  • Arun Gowtham
  • Nov 1, 2021
  • 1 min read

SRE Ottawa hosted James Li, RAMS Engineering Lead, Parsons Inc., Kingston, Canada on October 27, 2021, during its seminar event#335. James presented the group on the topic of A Glance at Monorail System Safety, and lead an active discussion on the various safety analysis tools available for Reliability Engineers.


Monorails have found a niche segment in the public transportation plans of major cities and commercial sites. James underscored the importance of Safety in the design of any complex system and the simplicity of monorail is deceiving its need to have a breadth of analyses done. The industry has developed the Monorail Transit System Safety (MTSS) philosophy to address the potential hazards. Combined with the standards established, this calls for the application of a variety of safety analysis tools such as System Safety Program Plan, Hazard Analysis, Fault Trees, FMEA, Sneak Circuit Analysis, Common Cause Failure Analysis, Software Safety Assessment.


These tools are used in different phases of the product design cycle to appropriately capture the safety risks of each system/component/interaction. Completion of these analyses then starts the approval process that independently verifies the assessment and gives the final nod for the designed monorail system to be installed. As evident from the presentation, there are many ways to conduct a safety assessment of a monorail system and it gives the engineers working on these to use their experience in choosing the optimal tools. For more information on how to apply these tools or any safety-related questions, contact us to get access to James Li's presentation recording.



  • Arun Gowtham
  • Oct 5, 2021
  • 2 min read

Updated: Feb 2, 2022

SRE Ottawa hosted seminar#334 on 29th September 2021 and had the pleasure of welcoming Chris Hobbs, Software Developer, Certified Systems/BlackBerry QNX. Chris is a previous winner of Colin Chabot Memorial Award and at this webinar presented ideas on Handling intellectual debt in Reliable Systems.


Intellectual debt is a term describing the lack of understanding of the principles behind a process or an event. i.e. we know something works but we don't know why it works. One introductory example cited by Chris during this webinar is the invention of the drug Aspirin. It was discovered in 1897 but the explanation of how it works was given in 1995, accounting for an intellectual debt during all these intermediate years. This debt, as any debt in any form, has its consequences. Without fully comprehending the mechanism behind a function, we accept the risk to utilize it or hinder further enhancement of the function. Either of which is undesirable.


In the context of Reliability Engineering, an intellectual debt can arise in the following instances: a product fails and the root cause is unknown, a complex system stops working after a software update, a predictive algorithm correctly predicts equipment's failure without explaining the influencing factor. While Reliability tools such as RCA, FRACAS can help with the first two cases, the issue gets acute with machine learning applications. Though the algorithms used in improving the Product Reliability and Asset Management are not as sophisticated as used in general AI systems, the decisions driven by the outputs of these algorithms should be assessed appropriately to forestall the intellectual debt from accruing. The correlation models fitted by the data should be audited for its prediction and explained by the engineers using theory. The more critical the effect of decisions from these models, the more rigorous the audit should be. Models built to compute values on the interaction with other models shall have control limits to trigger examination. But can all the processes be explained by a foundational theory?


Learn more about how to handle the intellectual debt in reliable systems from Chris Hobbs' in-depth presentation. A recorded video is available for SRE Ottawa members. Check out the membership page for details.

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