(648h) A Framework for Incorporating Strategic Asset and Product Decisions in Integrated Planning and Scheduling

Integrating different levels of decision-making has been a long-standing problem in Process Systems Engineering (Maravelias and Sung, 2009; Garcia and You, 2015; Dias and Ierapetritou, 2017). Most prior literature in the area of integrated planning and scheduling tackle the reconciliation of tactical and operational levels. Kallrath (2002) studied integration of strategic and operational planning in the chemical industry, but the strategic decisions considered are limited to supply chain planning. In this work, we focus on integration of strategic and operational level decision-making while exploring a wider array of strategic choices that often arise in real-world process industries.

A majority of multi-asset and multi-product batch facilities in the process industry are very dynamic in that product mix, recipes, capacities, and network configuration evolve frequently over time. Strategic asset and product portfolio planning must consider long-term growth opportunities while including decision-making related to all the above factors. However, the success of these strategic decisions crucially depends on how well they can be implemented given operational constraints.

Suggestions for strategic and capital projects can arise from R&D (e.g., new processes, new catalysts), Product Management and Marketing (e.g., new product opportunities), Supply Chain and logistics (e.g., supply network debottlenecking opportunities), and Manufacturing functions (e.g., manufacturing efficiency improvements), and often only a subset of these projects are chosen. As such, there is a need for frameworks that can screen all options and recommend the right set of strategic decisions over time with the expectation that manufacturing and supply chain operations will be able to execute on them while avoiding over-investment.

In this work, we consider a multi-product, multi-asset batch facility along with associated inventory and logistical capacities. Long-term projections for product families are available, but product families are differentiated into product groups within the production train, and prior to storage. At the strategic level, we consider decisions including (1) introduction of new products, (2) introduction of assets and storage tanks, (3) expansion of production capability of assets, and (4) long-term production targets and product mix based on demand projection.

On the operational level, several details are considered. Sequence-dependent changeovers for products are considered in the context of finding feasible cyclic schedules. Cyclic schedules are deemed feasible if constraints relating to storage capacity, expected monthly demands, and inventory turns are satisfied. This also has implications on the downstream tank farm in terms of product-tank allocations and the potential need for new asset-tank connections.

We decompose the problem into two levels, where a strategic planning model is solved at the master level and the feasibility of the underlying operational model is checked in the sublevel. According to the result of the sublevel we add optimality or feasibility cuts to the master level and iterate until decisions in both levels converge. We propose novel constraints to model various strategic choices as well as to account for the number of inventory turns targeted by supply chain organizations. We also propose production target constraints that the cyclic schedule in the operational level must satisfy on average, an aspect that has not been considered in the literature.

Through industrial-scale case studies, we show that optimizing strategic decisions while considering operational constraints significantly reduce the risk of strategic projects failing, leading to significant cost savings and improved long-term profit.

References

Kallrath J., Combined strategic and operational planning – an MILP success story in chemical industry. OR Spec. 2002, 24, 315-341

Maravelias, C.T.; Sung, C., Integration of production planning and scheduling: Overview, challenges and opportunities. Comp. Chem. Eng. 2009, 33, 1919-1930

Garcia, D.J.; You, F., Supply chain design and optimization: Challenges and opportunities. Comp. Chem. Eng. 2015, 81, 153-170

Dias, L.S.; Ierapetritou, M.G., From process control to supply chain management: An overview of integrated decision making strategies. Comp. Chem. Eng. 2017, 106, 826-835