Objectives of the workshop
This interactive and engaging workshop aims to produce research directions for the community concerning the application of Artificial Intelligence (AI) in Supply Chain Management (SCM).
To accomplish this goal, the workshop will warm the attendees up with a few short talks about current supply chain challenges. Then, attendees will be invited to participate in a guided and interactive brainstorming session to gather ideas regarding practical applications of AI in supply chain management. Then, they will be divided into groups to discuss and build consensus on the categorization of ideas, and tag the ideas with maturity, challenges, and research opportunities.
The following is an example list of SCM areas where participants can think of applying AI:
- Visibility and Transparency
- Demand forecasting and planning
- Inventory management
- Logistics and transportation optimization
- Supplier relationships and sourcing
- Warehouse automation
- Quality control and risk management
- Process automation
- Risk management
- Information management
- Systems integration
The workshop aims to provide a platform for open knowledge exchange between industry experts, academics, and professionals to foster innovative thinking and strategic collaboration in AI-enabled SCM. The workshop organizers plan to produce a report based on information collected during the workshop, where all attendees will be acknowledged as contributors.
Formats and duration
Duration: 3.5 hours
Format: Hybrid mode (Online participation is possible for speakers, and on-site only for participants in the interactive section). The role of the speakers is to provide practical case studies/ insights from their own research or businesses, which support workshop participants to grasp an overview of possible AI applications in SCM. Conditions for attending the APMS’s workshop must be clarified for Speakers before reaching them.
Participants: Researchers, faculty, students, and industry experts in supply chain, logistics, and artificial intelligence.
Agenda overview
Opening Remarks (5 mins)
- Welcome & Workshop Overview
Talk on What AI means in Industry Today
- Dr. Soundar Kumara, Allen E. Pearce and Allen M. Pearce Professor of Industrial Engineering, Penn State University
Warm up Talks (60 mins total | 3 speakers x 20 mins each)
Topics of Talk:
- Key supply chain challenges in biopharmaceutical manufacturing. Mr. Stephen Wing. Principal Business Development Manager, Electronic Data Exchange, Merck KGaA Life Science Business.
- Challenges and Opportunities in Applying AI in Supply Chain (Google’s Practical Best Practices for the Industry). Dr. Jaewook Kim, Senior Software Engineering Manager, Devices and Services Product Group, Google.
- AI in the Yard Industry. Dr. Jo Wessel Strandhagen, Research Scientist, Technology Management, SINTEF.
All these topics provide insights into challenges from a business, engineering, and regulatory compliance perspective that inform the workshop participants.
Workshop exercises and breaks (120 mins)
Theme: “Unlocking AI Potential across SC landscape (SCOR model: Plan, Source, Make, Deliver, Return”) can be used as a guide for brainstorming and grouping people based on their interests and backgrounds.
Participants: All participants attended this round.
Process: The process may be conducted physically using a post-it or digitally using tools like Stormboard
- Proposal Stage: Participants are asked to write down up to 3 ideas about the application of AI to supply chain issues. Each idea should be tagged with one of SCOR activities most relevant to it, namely Plan, Source, Make, Delivery, or Return. The idea should be tagged with types of issues most relevant to it, namely Business, Engineering, or Regulatory Compliance. (10 mins)
- Normalization Stage Round 1: Divide into five groups (or maybe four groups with Delivery and Return together) according to the SCOR activities to read and understand the ideas with the aim to normalize the proposed ideas (15 mins).
- Break (15 mins)
- Clarification Stage: Each group has up to 7 mins to ask questions for clarification about proposed ideas (35 mins)
- Normalization Stage Round 2: Each group finalizes the idea normalization, which can involve merging, splitting, and revising the ideas for clarification (15 mins)
- Maturity Stage: Participants in each group vote on the maturity of the ideas using TRL scale (10 mins).
- Challenges Stage: Each group discusses and write down technical and research challenges in realizing each idea (25 mins)
- Closing and remarks (5 mins)
Deliverable: Post-workshop Report
A report summarizing key discussions, findings, and recommendations will be compiled and shared with participants. It will include:
- Speaker contributions
- Brainstorming outcomes
- Identified use cases and solutions
- List of attendees and affiliations
Expected outcomes
The following outcomes are expected from the workshop, which aims to enhance the know-how of SCM experts about AI applications in their field.
- Enhanced understanding of AI’s role in SCM
- Practical insights of AI applications in SCM in multiple processes
- Networking between experts and participants
- Actionable strategies to overcome AI adoption barriers
Contact: yen.mai.thi@fh-zwickau.edu