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Data Analytics for Process Industry Instructional Design

Tools and Techniques

Course Overview

Process manufacturers continue to invest in and implement a host of digitalisation tools to increase their Industry 4.0 maturity level and integrate and optimise most business processes. Workforce engagement, involvement, and identifying the new skills needed represent the key determinants of success in this transformation journey.

Most organisations are now initiating pilot projects to improve operations with advanced digital tools, scaling such pilots in entire operations and designing and building new plants based on the latest technological concepts.

According to Smuts et al. (2020), a strategic alignment between the key domains is critical to integrate a wide range of technologies, including data analytics, cloud computing, machine learning, artificial intelligence and many others. On the organisation front, Jerman et al. (2020) underlined that changes are essential regarding future job profiles and competencies. However, there are different perceptions about future jobs and competencies needed for Industry 4.0. Nevertheless, there is a general agreement that job profiles related to programming, mechatronics, robotics, data analysis, Internet of Things, design and maintenance of smart systems, process analysis, and bionics are the new job profiles needed in smart factory systems.

We have developed a training program on the management and integrity of big data and data analytics in this context. This program aims to develop key capabilities for a future-ready workforce that supports emerging technologies within the process industry.

 

KEY Learning Outcome

After completing this course, learners should be able to articulate the importance of data integrity for process industries. In addition, they will be able to discuss the principles of presenting data analytics project outcomes to the senior management and create a business case.

  • Learning 1: Introduction to data analytics in process manufacturing
  • Learning 2: Designing smart experiments
  • Learning 3: Deriving insights from manufacturing data
  • Learning 4: Drive data integrity and advanced data analytics with real business case

Class Size: Min 10 to Max 15

Course Duration: 2 Days (16 hours)

Who Should Attend: Process engineers, scientists, process managers working in process manufacturing industries.

Pre-requisitesHigh-school level mathematics, Knowledge of spreadsheet software such as MS Excel

CostSGD 1000 per pax

Mode of Delivery: Hybrid (E-learning + Instructor-Led Virtual Training)

Certification: Certificate of Attendance

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