Sunday, August 6, 2023

Operational Analytics - Industrial Engineering Measurement & Analysis


Industrial Engineering Measurements - Online Course Module - Introduction and Index


Industrial engineering and productivity improvement use records of daily work and analyze the data. In the area of data analysis, analytics is the new area. Earlier sample based statistical inference was used for decision making and industrial engineering discipline adopted sampling based data collection and analysis. Now the current methods use full data and analyze. This area is being called analytics. Industrial engineering discipline started adopting the new method and IISE launched an initiative to provide education and training to practicing IEs.



IISE Initiatives



IISE OPERATIONAL ANALYTICS CERTIFICATION

14.0 CEUs

OVERVIEW:

This course provides the broad, comprehensive, and in-depth knowledge and skill base required to make a difference for organizations in the area of Operational Analytics.  You’ll be exposed to two structured models and methods/roadmaps for designing and creating effective Performance Measurement Systems.  There are 10 Modules, the 10th is the final exam and the certification project.  You’ll be walked through a systematic method for doing Operational Analytics and provided with practice/exercises to ensure you do more than just know new things, you’ll build your skill sets also. The course curriculum is a blended model that includes video recordings that have developed specifically for this course from Thought Leaders and Subject Matter Experts in the field from Intel, IBM, Ford, Moresteam, The Poirier Group and others.  You’ll also have access to outstanding case examples that are Integrated LeanSigma Success Projects but also have strong Operational Analytics Components.  And, the course provides “Coaching Huddles”, opportunities for you to interact with our Course Support Specialists.

WHAT YOU WILL LEARN:

This 140-hour, 10 module program is self-paced and intended to be completed in 3-6 months.  At the completion of the program, students will be able to:


Create powerful charts/graphs and slides that portray data and facts in impactful ways.

Understand how to create visible and effective measurement systems to support process and organizational performance improvement.

Be an effective Data Manager and an effective Data Analyst.

Use data analytics tools (like Minitab) effectively and with confidence.

Understand how to integrate Operational Analytics with the Study-Adjust process (for example, how to create Huddles and then build Huddle Boards and Dashboards to drive continuous improvement in an organization).


COURSE CONTENT

The course is composed of ten core modules plus one bonus module:

Module I—Overview of the Certificate and Certification Program, Syllabus, Plan of Study, Assignment List, etc.

Module II—Op Analytics:  Perspectives and Overview

Module III—Op Analytics:  The Data Management Role

Module IV—Op Analytics:  The Analyst Role

Module V—The Data Scientist Role

Module VI—Op Analytics:  Process Improvement (Measure/Analyze Stages of DMAIC)

Module VII—Op Analytics:  Visible Measurement/Management Systems

Module VIII—Engineering Management Systems

Module IX—Case Studies

Module X—Final Exam and Certification Project

Module XI—Bonus Module—Integrated Systems Engineering and Business Excellence and Continuity/Op Excellence


https://www.iise.org/TrainingCenter/CourseDetail/?EventCode=OAO


OPERATIONAL ANALYTICS - NEW FRONTIERS FOR ISES

Presenters: Ben Amaba, Ph.D., IBM and D. Scott Sink, Ph.D., Ohio State University


This is yet another offering from Chapter No. 1 in our series on Operational Analytics. The focus in this one-hour session is on operational analytics to include automation of analytics — AI as well as data and implementation sciences as a New Frontier for ISEs. We’ll continue to utilize the Intel Analytics Triangle and Management Systems Model as our organizing frameworks, those work well. We will also build on some nice work happening at the University Health Network in Toronto, Canada. We’ll also build on the nice presentation that Matheus Scuta from Ford did overviewing Ford's approach to integrated operational analytic.


Ben Amaba is our featured speaker; Scott will be more of a color commentator and will tee up the webinar. Ben is the global chief technology officer (CTO), data science and AI elite team, industrial manufacturing for IBM. One of his interests is the intersection of ISE and Industry 4.0 and Data/Operational Analytics.


What we will focus on is how ISEs can contribute and in some cases make a great career in the operational analytics field. We’ll discuss the emerging field of what’s called data and implementation sciences. The ability to get the right data, organize it properly, analyze it quickly and effectively and drive through to solutions that are effectively implemented is super critical in today’s fast paced world. We’ll help you understand and frame up this evolution.

OPERATIONAL ANALYTICS: THE DATA MANAGEMENT ROLE

Jared Frederici, Scott Sink and a few other thought leaders will walk you through the next step in Operational Analytics, the Data Management Role. We’ll go back to the Analytics Triangle and work you through the bottom half of that methodology. We’ll explain and discuss data capture, data organization, data integration, data cleansing, readying data for analytics, "wrangling," slicing and dicing, and other Data Management requirements. It’s a huge field of study but we’ll give you a solid overview as a foundation for continued learning and development.



OPERATIONAL ANALYTICS FOR INTEGRATED LEANSIGMA PROCESS IMPROVEMENT PROJECTS

Presenters: Jared Frederici, The Poirier Group and Scott Sink, The Ohio State University

ILSS improvement projects require a different type of operational analytics than most organizations are used to applying and using. Scott Sink and Jared Frederici will utilize a variety of different case studies (specific ILSS projects) to provide guidance for process improvement specialists as how to build and execute measurement and analysis plans to support process improvement and sustain improvements over time.   
https://www.iise.org/details.aspx?id=45487


OPERATIONAL ANALYTICS FOR INTEGRATED LEANSIGMA PROCESS IMPROVEMENT PROJECTS - PART II
Presenters: Jared Frederici, The Poirier Group and Scott Sink, Ohio State University

Part II of our Operational Analytics (OA) Series focuses on the data management role of an ISE in a process/performance improvement project. Frederici will lead by sharing a data modeling process that ensures you have the right data and facts to support sustained process improvement. We will share case examples from real DMAIC projects to bring concepts to life. This will tee up Part III in June which will focus on the Analytics/Analyst and Decision Support role in OA.   
https://www.iise.org/details.aspx?id=46164


OPERATIONAL ANALYTICS FOR INTEGRATED LEANSIGMA PROCESS IMPROVEMENT PROJECTS PART III

Presenters: Jared Frederici, The Poirier Group and Scott Sink, The Ohio State University

Part III of our Operational Analytics Webinar Series focuses on the Decision Support Analyst role. We will review, summarize parts I and II first, and then zoom in on the art and science of creating powerful visualizations that can accelerate improvement decision-making and action-taking. Practical case examples are provided from the more than 300 projects we both have worked on in the past 10 years. 
https://www.iise.org/details.aspx?id=46674

OPERATIONAL ANALYTICS FOR INTEGRATED LEANSIGMA PROCESS IMPROVEMENT PROJECTS  PART IV

Presenters: Jared Frederici, The Poirier Group and Scott Sink, Ph.D., Ohio State University

Part IV of our Operational Analytics Webinar Series will capstone the first three parts, bring it all together. We will discuss comprehensive case examples of where the Data Manager Role (Part II) and the Decision Support Analyst Role (Part III) come together in DMAIC and/or DCDOV type Process Improvement Projects. We’ll have project leaders on the webinar with us in a panel type format and will engage the audience in Q&A.
https://www.iise.org/details.aspx?id=46782

Videos

Operational Analytics 101: Foundational Principles & Frameworks You Can Build From | Full Length

The Poirier Group
June 2023
https://www.youtube.com/watch?v=2qknGbG4Z9k


Others


Published on June 4, 2022
What is Operational Analytics and its business use cases?
Operational analytics focuses on monitoring the current and real-time operations.
By Sourabh Mehta
https://analyticsindiamag.com/what-is-operational-analytics-and-its-business-use-cases/

Use Cases

Uber & Ola
Operational Analytics is used by  Uber & Ola to  select the most convenient passenger pickup spots and to project the shortest routes.

Online merchants
Operational Analytics is used by online merchants to evaluate which goods are the most popular in their stores and modify inventories appropriately. They also analyze  real-time data on customer searches and develop hot trends.


Finance
Operational Analytics is used by banks and financial institutions to detect fraud and liquidity risk. They are given the task of analysing client spending patterns and identify anamolies. 

Manufacturing
 Manufacturing businesses employ operational analytics to identify items likely to fail and initiate predictive maintenance of machines, machine components, and other assets to detect possible issues before they arise. The manufacturer can be notified when servicing is necessary using this information.

Supply Chain Management
The use of operational analytics in the Supply Chain gives employees well-structured dashboards containing vital data, which they can analyse and promptly agree on a supplemental delivery with the Supplier in case of missed delivery dates.      

Marketing
A marketing manager  may use operational analytics to run numerous experiments to understand likely success of various market moves. He can terminate unproductive trials, and nurture the ones that succeed.  

Optimizing products
A product manager looks at product-usage logs provided by operational analytics to determine which features of the product are liked by its users, which features slow them down, and which features are disliked by its users.



Business analytics in manufacturing: Current trends, challenges and pathway to market leadership

Yamila M. Omar, Meysam Minoufekr, Peter Plapper

Operations Research Perspectives
Volume 6, 2019, 100127

https://www.sciencedirect.com/science/article/pii/S2214716019300934


Videos

Operational Analytics 101: Foundational Principles & Frameworks You Can Build From | Full Length

The Poirier Group
June 2023
https://www.youtube.com/watch?v=2qknGbG4Z9k

Big Data Analytics and Visualization for Productivity.
Asian Productivity Organization.


Manufacturing Analytics



Manufacturing Analytics - Introduction - Bibliography

Machine Tool Analytics - Analytics for Machine Tools


Cloud-based Manufacturing Analytics: Case and Barriers
5-MINUTE READ SEPTEMBER 01, 2022


Cloud-based Manufacturing Analytics: 4 Keys to Success
5-MINUTE READ SEPTEMBER 08, 2022



Ud. 6.8.2023

Pub 4.8.2023






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