The aim of the course is design processes and products using advanced mathematical programming tools (LP, NLP, MILP, MINLP & multiobjective optimization) and process simulation as design support tools. The course will focus on problem-based learning, with a pletora of different, diverse, multidisciplinar and crossdisciplinary cases affecting products of high/low added value, and also including aspects like planning, logistics, scheduling...

The topics covered in the course are:

1. Fundamentals of product and process design.

1. Why modelling?

2. Fundamentals of optimization

2. Product and process design using mathematical programming & optimization. Decision support tool: solver MSExcel

1. SolverExcel Training: toy examples

2. Examples:Power generation. Allocation. Allocation with carryover. Cutting pieces. Logistics: 2 echelon supply chain. Logistics: 3 echelon supply chain. Facility closing. HHRR scheduling. HHRR scheduling with workers preference. Process synthesis: superestructures. Dynamic optimization.

3. Scheduling of batch processes:

1. Scheduling of batch processes: flowshop, Jobshop, productcampaign, transfer policies,

2. Design and retrofit batch processes: Beer batch production

3. Paper and pencil case studies.
4. Batch product and process design. Decision support tool: SuperPro

1. Modelling batch processes: decision making.

2. Super Pro minitutorial. Case studies.

3. SuperPro workshops.

4. Case studies: beta galactose, WWTP, SPD, continuos, cost analysis, databanks, MAB, brewery, carrageeenan, corn refinery, WFI.
5. Product and process design using mathematical programming & optimization. Decision support tool: GAMS,

1. Introduction to optimization and NLP

2. Process Optimization: Linear Programming

3. Paper and pencil case studies.


NOTE THAT CHANGES IN THE SCHEDULE, AGREED WITH INDUSTRIAL LEADERSHIP, WILL BE PUBLISHED IN MOODLE BEFORE THE COURSE STARTS.