Digital Supply Chain Optimization Trends in Refining and Chemicals Industries

A conversation with Alan Kosansky, co-founder and President of Profit Point

April 12, 2022

AspenTech and our Implementation Services Providers (ISPs) are helping customers on their supply chain digital transformation journeys. I recently had a conversation with Dr. Alan Kosansky, co-founder and President of Profit Point, an AspenTech supply chain ISP, to get his perspective and insights on planning, scheduling and optimization project trends in the refining and chemicals industries.

Roch Gauthier (RG): Hello and welcome Alan. If you could, please share a bit about yourself and Profit Point and your team’s expertise and experience in delivering Aspen Supply Chain Management (SCM) planning, scheduling and optimization solutions.

 

Alan Kosansky (AK): Hi Roch and thank you for having me. I have personally been delivering Aspen SCM solutions for 28 years. In fact, it all started when I was an employee at Rohm and Haas Company (acquired by Dow Chemical in 2008) leading the team that selected Aspen SCM as the technology to support supply chain network design analysis across 10 business units, which quickly expanded to production scheduling implementations of Aspen SCM. I am proud to say that 28 years later, Profit Point is still supporting about 50 Aspen SCM models at Dow Chemical, and we continue to rollout to new sites. Today, our expert team of seasoned supply chain professionals are designing, implementing and supporting solutions for many companies across the globe and industries including chemicals, refining, food and beverages, pharmaceuticals and automotive.

 

RG: Oil and gas companies have historically focused on “inside the fence” supply chain processes such as crude purchasing and refinery planning and scheduling and AspenTech is now seeing an increased interest related to “outside the fence” supply chain processes. Can you share some highlights of Aspen SCM implementations Profit Point recently completed in this area?

 

AK: We delivered an Aspen SCM solution for a major oil company that enabled them to take their refined products vessel planning and scheduling process to a whole new level. The complexity of the tradeoffs between vessel costs, inventory costs, storage constraints, and vessel movement made it hard for them to make realistic schedules very frequently.

 

The Aspen SCM optimization model we implemented forecasts three to four months ahead and has enabled the company we serviced to reduce vessel chartering and fuel costs all while maintaining adequate inventory levels of each grade, at each port, without overflowing their storage tanks. Their process is now more integrated into their business decision making, with automated daily inputs of vessel locations, status and daily inventory positions across their primary distribution network. Now they can generate schedules each day based on updated inputs, analyze the cost impact of different decisions, and manage a complex process quickly and efficiently. We also implemented an Aspen SCM annual strategic model, which they use for appropriately sizing the storage tanks at the ports and when requesting leases.

 

Based on this success, we are now preparing to implement Aspen SCM for their in-bound crude vessel planning and scheduling process.

 

RG: Some integrated petrochemical and polymers companies aspire to synchronize planning and scheduling more closely across their value chain. Their goal is to better respond to the inevitable supply/demand changes. Can you share some highlights of Aspen SCM implementations you are delivering in this space?

 

AK: We are working with a large olefins and polymers (PE & PP) manufacturer that operates several cracker units to make the olefins, as well as multiple polymers production lines. Their key goal is to achieve higher customer service levels and higher throughput on their assets by having a greater level of interconnectedness between their polymers and crackers scheduling processes. A second goal is to be able to rapidly understand the impact on KPIs due to unplanned production upsets, or if they accept new opportunistic demand. Finally, they want to be able to rapidly reoptimize the allocation of demand and monomers to their various plants and production lines while staying within the capacity of the cracker units for monomer consumption. The extended scheduling solution we are implementing for them will enable their polymers demand to drive the cracker operations, making the best use of the feed stocks available.

 

RG: Many specialty chemicals companies are embarking on digital scheduling initiatives to improve customer service and return on assets. What some companies don’t appreciate is that scheduling is an area where details matter tremendously to capture business value. Can you share some perspective on this topic?

 

AK: I completely agree that scheduling is an area in which details matter a lot. The flexibility of Aspen SCM has allowed Profit Point to model equipment and process details in ways that no other software allows.

 

Have equipment that is not in the ERP system? No problem! Have shared equipment with limited capacity? Have count-dependent or sequence-dependent cleans, or both? No problem! Any of these details might determine the effectiveness of the schedule, turning it from friendly scheduling advice to good, productivity-improving, marching orders.

 

Do you pack out materials from the reactor? If so, that blocks the reactor during the pack out. What about when the pack out duration is variable based on the mix of packaging (pail or drums or totes). No Problem! Whereas we have seen first-hand these types of complications pose issues for other software, we have modelled them using Aspen SCM to achieve more realistic production schedules that allowed customers to increase production throughput by 5% or more.

 

RG: Thank you Alan for sharing some valuable insights with our audience.

 

To learn more about Profit Point’s Agile implementation approach to supply chain planning and scheduling software, download this white paper.


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