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

Presenter Information

Dr Mohammad Humyun Fuad Rahman

Dr Mohammad Humyun Fuad Rahman received his PhD in Computer Science in 2015 from UNSW. After PhD, he had the opportunity to collaborate on a project with Airbus Defense and Space (one of the leading European Industry) where he had the opportunity to develop decision support systems for autonomous material delivery systems to transport materials in defence and commercial supply chains. The project is also associated with developing a simulated environment, which is also key for Industry 4.0 and Industry 5.0 era. Apart from that, he is collaborating with the top researchers globally, who works in solving human-robot collaboration in production environments, and those works are in line with Industry 5.0 concept. Dr Rahman also studies integrated decision-making processes in the supply chains. He is a regular reviewer for top-tier manufacturing and Operations Research journals, where he reviews the paper relevant to manufacturing system optimizations, projects, and supply chain management with Industry 4.0 technologies. Considering the importance of advanced technologies in mitigating the unprecedented events that occurred due to the ongoing COVID-19 pandemic, he has served as a guest editor for Robotics and Computer Integrated Manufacturing journal, which is one of the top tier journals for manufacturing (title: Smart and Responsive Manufacturing to Mitigate Market Uncertainty). This has reinforced his ability in editing special issues associated with the COVID-19 pandemic. As an active educator, Dr Rahman delivers courses that are designed within the framework of modern technologies and he aims to assist his students to develop critical thinking ability to solve engineering problems while considering modern technologies. 

 

DR CHAKRABOTTY Ripon

Dr Ripon K. Chakrabortty (Member, IEEE) is the Deputy Director (acting) of the Capability Systems Centre (CSC) and 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 Cross-Disciplinary Optimisation Under Capability Context Research Team. He obtained his PhD from the UNSW Canberra at ADFA in 2017, while completed his MSc and BSc from Bangladesh University of Engineering & Technology on Industrial & Production Engineering in 2013 and 2009 respectively. 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

 

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)

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.