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.
Others
Manufacturing Analytics
Pub 4.8.2023
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