Digital twins + Theory of Constraints: Optimising Value Chain Management
Read time: ~5min
In today’s complex and interconnected industrial environments, managing and optimising value chains can be a formidable challenge. The Theory of Constraints (TOC) offers a powerful framework to identify and manage constraints that hinder a system’s ability to achieve higher throughput.
Coupling TOC with digital twins - virtual replicas of physical systems and processes - enables continuous monitoring and improvement of operations. This article delves into how digital twins and TOC can work together to address local and global losses in value chains, focusing on three key points: the prevalence of local losses, the role of buffers, and the importance of measuring losses against plans and capacity.
Local Losses across Value Chains
Value chains, composed of interconnected processes and activities that compose a production system, are susceptible to various constraints that can reduce overall system performance. These constraints can occur at any point in the value chain and often manifest as local losses. Local losses refer to inefficiencies or bottlenecks that occur at specific stages of the production process and are contained within a value chain, usually by a buffer. For instance, a delay in material transport or a malfunctioning machine can cause localised disruptions, impacting the immediate process but not necessarily the entire system. In a mining operation, for example, local losses might include delays in ore extraction due to equipment failure or suboptimal scheduling, but are spatially and temporally contained by an ore stockpile. i.e the loss is local to the value chain and accompanying buffers. These local losses, while seemingly minor, can accumulate and impact overall production efficiency.
Geminum’s digital twin technology visualises real-time constraints at a mine site, enabling proactive management and optimisation of value chains.
Digital twins, with their ability to continuously monitor across all value chains, and their ability to back propagate local losses in one area to the historic process variation that caused it, can help identify and quantify the global impact of these local losses in near real-time, allowing all managers on and off site to see and address issues promptly.
Buffers and their Role in Managing Losses
Buffers are essential components in managing variability and ensuring smooth operations in value chains. They act as temporary holding areas for production materials, absorbing the impact of local losses and preventing them from cascading into more significant disruptions. However, if these buffers are penetrated frequently and cumulatively, they can transform local losses into global losses, affecting the entire system’s performance.
In mining, buffers such as ore stockpiles or equipment standby capacity are crucial. They provide a cushion against unexpected delays or breakdowns. For instance, if an excavator breaks down, a buffer of pre-extracted ore can keep the processing plant running without interruption. However, if the breakdowns are frequent and the buffer gets depleted, the entire operation can grind to a halt (a global loss), often days or weeks after multiple local losses.
Digital twins can play a pivotal role in buffer management. By continuously monitoring buffer levels and simulating proposed production plans, they can predict significant buffer penetrations or lower than required buffer levels (e.g. for upcoming shutdowns) and alert managers before these local losses aggregate into global losses. This predictive capability enables proactive measures to adjust operations, ensuring continuous and smooth production flow, or at least providing insight into future plan changes that are required to avoid or mitigate significant global losses.
Measuring Losses: Insights into Plan Setting & Capacity Utilisation
To effectively manage and mitigate losses, it is essential to measure them against both the plan and the system’s capacity. This dual measurement provides valuable insights into the effectiveness of current plans and the true capacity of the system, highlighting areas for improvement.
Measuring losses against the plan involves comparing actual performance with the planned targets. This comparison helps identify deviations and understand the reasons behind them. For example, if a mining operation planned to extract 10,000 tonnes of ore but only achieved 9,000 tonnes, the shortfall can be analysed to pinpoint specific constraints or inefficiencies. These insights can then be used to adjust future plans, change processes, add or alter equipment, adjust resources or take other actions that are intended to optimise resource allocation.
On the other hand, measuring losses against capacity involves assessing how well the system is utilising its available resources. This assessment can reveal whether the system is operating close to its maximum potential or if there are significant untapped capacities. For instance, a processing plant might be set to operate at 90% capacity due to intermittent local losses, and fear of multiple excursions from plan and subsequent investigations. Identifying these deliberate under-utilisations allows managers to take corrective actions, such as reconfiguring workflows, investing in additional resources, or even changing the culture of what it means to not comply with plans.
Digital twins enhance this measurement process by providing a continuous stream of data and real-time analytics. They can track performance metrics, simulate different operational scenarios, and predict plan non-conformances. This continuous feedback loop not only accelerates root cause and reliability work, but also enables dynamic adjustments to plans and operations, ensuring that the system operates closer to its optimal capacity for more hours per year.
Integrating TOC & Digital Twins for Optimised Operations
The integration of TOC principles with digital twin technology creates a powerful synergy for optimising value chains. TOC provides the conceptual framework to identify and manage constraints, while digital twins offer the tools to monitor, simulate, and predict system behaviour. Together, they enable a holistic approach to managing local and global losses, enhancing overall system performance. The classic 5 focusing steps of TOC, as applied through and with digital twins, looks something like this:
Identify Constraints: Digital twins can continuously monitor operations, providing real-time data to identify constraints. By simulating different scenarios, they can predict potential bottlenecks and allow managers to address them proactively.
Exploit Constraints: Once identified, constraints should be fully exploited to maximise system utilisation. Digital twins can help optimise workflows and resource allocation, ensuring that constraints are used efficiently, and can monitor the unintended consequences up and downstream of changes made to the system.
Subordinate Processes: Other processes should be adjusted to support the identified constraints. Digital twins can provide insights into how different processes interact and suggest adjustments to enhance overall system performance. Examples include supplementary value streams such as water and power, where planned maintenance activities are sometimes isolated from their impact on production systems, due to organisational or contractual silos.
Elevate Constraints: If constraints continue to limit performance, they should be elevated through investments or process improvements. Digital twins can monitor the impact of these changes, helping managers make informed decisions about process and equipment changes, and verifying that the measured improvements are global in nature and not just local.
Prevent Inertia: Continuous improvement is essential to avoid complacency. Digital twins provide persistent and dynamic feedback loops, enabling ongoing monitoring and adjustments to operations.
Summary
The combination of TOC and digital twins brings together a powerful and proven framework with a persistent and real time tool to more effectively manage and optimise value chains. By focusing on local issues that create global losses, managing buffers effectively, and measuring losses against plans and capacity, organisations can enhance their operational efficiency and overall system performance. Digital twins provide the real-time data and predictive analytics needed to implement TOC principles effectively across short intervals, ensuring continuous improvement is embedded into daily operations.
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