Integrated Planning in the Coal Industry: Case studies on the simultaneous optimisation of processing strategies, stockpiling, and product strategies with BlendOpt

To remain competitive in today’s challenging market, coal mines will need to develop a holistic strategy for value creation as well as improve the coordination of operations planning across the coal supply chain. Plans for mining, processing, logistics, and marketing are difficult to align with enterprise objectives if each planning activity is developed separately instead of holistically. In practice, coal chain optimisation is only achievable through integrated planning. By integrated planning, we mean coordinated planning of decisions between mining, processing, logistics, and sales. While the importance of integrated planning is recognised, its execution is difficult without the right tools to support this process. This paper presents a technical analysis of BlendOpt: the first mathematical optimisation software tool that supports complete integrated planning of coal sales and supply chain strategies. Starting with a mine schedule, BlendOpt discovers strategies for how coal should be processed, blended, and allocated to different products or sales contracts with the objective of maximising profit. Mathematically optimised plans are created using algorithms that test millions of possible plans in search of the highest profit from the data provided. Previous mine supply chain optimisation software has historically been unable to accurately model the problem and did not contain algorithmic techniques that could solve the problem in a timely fashion. In addition, any results generated were difficult to analyse thereby limiting what insights could be gained to inform improvements to business strategy. These themes provide the lens through which BlendOpt’s technical capabilities are assessed in this paper. Defining the Right Problem: Solving the right integrated planning problem can influence whether operational decisions will align across a supply chain. To highlight this point, this paper reviews case studies where changes to the fidelity of sale price models and cost models significantly altered the financial optimality of processing and marketing decisions. Challenge Current Planning Assumptions: Challenging long-held planning assumptions and posing alternatives can sometimes act as a catalyst for realigning decisions across a supply chain. Using case studies, this paper compares existing intuition-based wash-bypass decisions at two Australian operations with mathematically optimised decisions derived by BlendOpt. Integrated Planning: A New Priority for the Coal Industry Market conditions will no longer allow for operations that are not competitive in costs and cash flow. While asset quality is paramount, competitiveness is also influenced by operational decisions made across a coal supply chain. The effectiveness of operational decisions is limited by their coordination and subsequent alignment. In other words, what is a good decision for each separate business unit depends on those decisions made within other units. Silo business drivers for mining (ROM tonnes), processing (utilisation), and marketing (revenue) only align with enterprise objectives (cash flow, NPV) when operational performance is low. Under high performance operating conditions, decisions guided by silo KPIs will misalign with the interests of the group and erode value (March, 1991; Levinthal and March, 1993). This is particularly true of coal processing decisions and their interdependency with decisions in mine planning, logistics, and market planning. Decisions in coal processing impact coal quality, product specifications that can be achieved and thus sold, production yields and operating costs. While maximising plant utilisation and “washing to an ash spec” instead of blending to an ash spec have known limitations, today’s tight margins are revealing more subtle and deeply held assumptions about what product a coal ‘should be’ that become invalidated as revenue approaches costs. In practice, coal chain alignment requires the coordinated planning of decisions between mining, processing, logistics, and sales. While the importance of integrated planning is recognised, its execution can be challenging. Understated difficulties arise in data integration and technical challenges arise in the creation and optimisation of an integrated plan (King, 2004; Whittle, 2010). Also important are the organisational challenges to realising effective coordination at every stage of the planning process from agreement on scope, procedures for plan development, plan refinement and execution. While such challenges were relatively less important in a high margin operating environment, today’s coal industry faces a convergence of challenging conditions that increase the importance of integrated planning. In particular, integrated planning becomes more significant as easy access high-quality single seam operations are replaced by more complex multi-seam operations and also as price compression across some metallurgical and thermal products creates new questions about how a producer should process, blend and market their coal resources. Review: Integrated Plan Modelling Requirements When undertaking a planning exercise, it’s important to model only those constraints and problem features that significantly influence the calculated performance of a plan. When relevant problem features are ignored, the performance of decision options will not be accurately evaluated and can become misaligned with the actual financial metrics of an organisation. For instance, ignoring the difference in operating costs between washing coal and bypassing coal can bias mathematical optimisation in favour of higher quality products. This section reviews this and other relevant considerations when solving the integrated coal planning problem.