By David Reader, Director, Process.

Historically, mathematical modelling and simulation have been confined to sectors and projects with a focus on manufacturing, operations, logistics and supply chain. Despite the availability of the technology since the 1980s, the construction industry has been much slower to apply these methods; most likely due to the nature of building design, with one-time projects using many unique elements and few repeatable processes.

Discrete Event Simulation (DES) is a method of modelling a system by evaluating a series of activities at the time they occur, or by evaluation at set points in time (every second, for example) with no change assumed to have occurred between the time steps. This type of simulation is well suited for activity-based operational modelling where the complexity of continuous simulation is not required.

DES is typically used to understand and improve the performance of a system, in the research and development or design phase, or for processes already in operation.

Bringing the construction industry up to speed with DES

Research in the sector has found that while construction-related spending is 13% of global GDP, productivity has been flat for decades – with an ageing workforce and additional post-Brexit losses affecting the UK. Similarly, construction accounts for a large portion of global waste and carbon emissions, but is yet to see large improvements. With Discrete Event Simulation previously a niche activity requiring a specific skill set and often costly software, the industry has not been able to see and leverage the benefits, which include predicting the full effects of a project – whether related to efficiency, cost or the environment – until site work is completed.

A recent shift in the construction landscape has been an increasing focus on Design for Manufacture and Assembly, or DfMA, which aims to improve the efficiency and effectiveness of the construction centre, improving productivity, reducing waste and aiming for net-zero carbon emissions. Bryden Wood have been pioneers of DfMA and successfully delivered benefits around the world with Platform Construction (P-DfMA) and other types of solutions [constructionplatformsforasia/s90575/] using a Design to Value approach [designtovaluest/s93816/]. DfMA itself can be based on a set of repeatable elements and processes to derive gains, and ultimately could transform the construction industry so that it more closely resembles manufacturing. With Industry 4.0 now a key part of many sectors, research and development into construction automation is also a rapidly growing area. Additionally, the skill sets required to implement methods such as Discrete Event Simulation are becoming more commonplace as the industry steadily adopts more facets of digital design.

Despite the advances, construction planning is still typically done using static Gantt charts which, although highly detailed, often have the potential to be inflexible, inefficient and inaccurate, and cannot allow stakeholders to explore fully and rapidly the ‘what if’ of projects and the effects of their decisions on the final product. A lack of clear visualisation can also limit the communication of the planning to the project team and again result in an unclear relationship between project briefing, design and execution. With concept and design project stages – where this work is often done – being where the largest potential gains can be made, the power to positively influence a project with thorough optioneering to reduce risk and increase predictability is crucial.

Creating flexible, digital models that reflect the world around us

This is where the real strengths of Discrete Event Simulation (DES), or time-based process simulation, can be brought in. Using tools such as Lanner Witness or AnyLogic, a digital model can be created from the macro to the micro scale, including global supply chain and logistics, down to individual site operations. Digital models built within these tools are made with the logic and rules necessary to represent the real-world process and constrain the system. These are typically based around the flow of operations, their dependencies and the resources required to complete them. However, one does not need to rigidly prescribe any of these aspects in detail, or hard-code them, to derive the results, but rather use the simulation engine to logically sequence operations and how resources are used.

A simple example of this could be a set of assembly operations occurring simultaneously, which use both shared components – bolts, for example – and resources, such as an operator or a wrench. Creating this model in a simulation tool would require defining individual assembly sequences and required resources at each step, the resources available and, depending on the requirements of the project, component stock, transport, and necessary aspects of the supply chain. When the model is run, the simulation engine dynamically uses resources and components to complete the tasks and the model statistics derived could indicate how both individual processes, and the system, would perform.

Ultimately this also allows for modelling flexibility as operations sequences, rules and resource information can be loaded from external files and changed dynamically during model runtime. Similarly, the highly visual nature of these tools can provide direct feedback to users while the simulation is running, or export data which can then be visualised in another tool (such as Tableau or Power BI). Analysing this data can then help not only to understand how a supply chain or site might perform, but also to anticipate bottlenecks early and mitigate them. Applying the core tenets of Design to Value, a modelling strategy can be developed which connects the project brief and client aims to the performance of the final product, measuring options against appropriate KPIs to improve performance and reduce risk.

Practical applications to drive efficiency with DES and DfMA

Recently, we have applied Discrete Event Simulation (DES) in a project for the rapid DfMA construction of storage and distribution facilities, building flexible, digital models that can represent both the on-site assembly sequences and the supply chain operations for the construction of multiple sites in Europe. In doing so we can validate and optimise the construction programme whilst also gaining insights into frequency and pattern of deliveries. This data can then be used to optimise stock quantities and locations, as well as discover any potential bottlenecks and options for alleviating these, to support the most efficient build sequence.

Bryden Wood has successfully applied these techniques to Platform construction (P-DfMA) and continues to do so for large clients. In using these Modern Methods of Construction (MMC) methodologies and tools we can slowly aid transformation and delivery value whilst addressing some of the most pressing sector and global issues which are faced today.


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