Supply Chain Analytics in Industry 4.0 era

Managing supply chains (SCs) is one key factor for many organizations, while new technologies and data-driven software solutions offer the policymakers the to optimize their decision-making processes. Diversification in local and global supply and distribution, increased customer expectations, increasing involvement of man and smart machines in the Industry 4.0 era, and enormous customisation of products results in a significant increase in complexity in the decision-making process. Consequently, traditional manual planning activities are challenged and there is a need to change the planning process within organizations. To overcome this challenge, decision-makers, at first sight, need to understand the benefits of supply chain analytics, in making a reasonable and reliable base for decision making for the modern SCs.

This short course will familiarise participants, especially those who engage with day-to-day decision-making in SCs or are interested to plan to follow that career path. This course and accompanying short case studies will facilitate both tactical and operational level complex decision problems under uncertainties.

No prior knowledge is assumed, however, basic skills in Microsoft Excel, and knowledge of High School level maths would be an advantage.

Duration: 2 Days

Delivery Mode: Live simulcast

What you will receive

UNSW Canberra certificate of completion/attendance
Masters credit: UNSW Canberra allows students who have successfully completed a minimum of 12 days of approved professional education courses to use those courses as credit in eligible postgraduate programs.

Who should attend

This introductory course is for anyone interested in solving decision problems in different supply chains for Defence, Government agencies, public and private sector organizations. This course is suitable for anyone faced with complex and dynamic decision problems in either public or private sector.

Presenter Information

Dr Ripon K. Chakrabortty (Senior Member, IEEE) is the lecturer on System Engineering & Project Management at the School of Engineering and Information Technology, the University of New South Wales (UNSW Australia), Canberra. He is also the program coordinator for Master of Decision Analytics & Master of Engineering Science programs in UNSW Canberra at ADFA. Dr Chakrabortty leads the optimisation and machine learning efforts in the Capability System Centre. He is currently the Group Leader of the Decision Support & Analytics Research Team. As an educator and active researcher in his field, his focus is to deliver authentic teaching by pursuing real-life and practical knowledge to diversified students. Inarguably, his research involvement in the discipline of 'Decision Analytics', 'Applied Operations Research', 'Systems Engineering & Project Management', 'Industry 4.O' aids him to expose knowledge gaps in the body of knowledge.

Whilst, his main role as an educator has been to augment the 'critical thinking skill' among students to bridge those gaps. He along with his team members have been making a good impact on applying different optimisation principles in artificial intelligence, electrical engineering, system engineering, project management and computer science domain. Such diversified research experience had made him successful in securing many big research grants. As a chief investigator, he has secured more than 2.5 million Australian dollars’ worth of research grant, while the apportioned amount to his credit is more than 1.1 million dollars. All his research grants have been from the Australian Defence Force (ADF).

Course Information

Course Outline

The course is divided into two modules (each for 1 day) as follows:

Module 1 (Day 1):

Fundamentals of the supply chain, e.g., explain the managing supplier selection, explain each tier of supply chain network: Supplier, transporter, manufacturer, retailer, customers.
Why Data analytics is important for modern SCs
Descriptive analytics: Descriptive statistics, Data visualization. For example, analyse the insights of production volume of a manufacturing plant.
Solving case studies.
All analysis will be done by EXCEL

Module 2 (Day 2):

Predictive analytics: Demand Analytics, Inventory analytics by time series analysis, and linear regression for demand prediction.
Prescriptive analytics: Linear and Integer programming models and use them in solving SC-oriented problems (e.g., transportation decision or product mix). Decision-making under uncertainty.
Solving case studies.
All analysis will be done by EXCEL

COURSE LEARNING OUTCOME

The participants will learn the fundamentals of modern supply chains and the role of data analytics in supply chains.
The participants will gain skill in using decision-making tools by Excel solver for solving case studies inspired from real-life.

Affiliated courses

Business Analysis and Valuation (professional course)
Decision Making in Analytics (program code: ZZCA6510)
Master of Decision Analytics (program code: 8634)

Cancellation policy

Courses will be held subject to sufficient registrations. UNSW Canberra reserves the right to cancel a course up to five working days prior to commencement of the course. If a course is cancelled, you will have the opportunity to transfer your registration or be issued a full refund. If registrant cancels within 10 days of course commencement, a 50% registration fee will apply. UNSW Canberra is a registered ACT provider under ESOS Act 2000-CRICOS provider Code 00098G.