Frances Sneddon, Data Scientist and CTO at Simul8, explores how digital simulation can provide the crystal ball that businesses need.

How do you loosen a lockdown? It is a challenge that governments across the globe are grappling with as they attempt to balance the necessity of kick-starting economies with the necessity of protecting people and productivity from the coronavirus pandemic. Digital simulation tools could be a crucial piece of the puzzle, helping businesses to rapidly test out the effects of different alterations to their workflows in a risk-free environment before putting them into practice.

Organisations will need to revisit their risk assessments and carry out an entirely new set of analyses to consider how previously run-of-the-mill processes and practices might need to be updated. While containing the further spread of COVID-19 is non-negotiable, opening things up again will require compromises at every turn, finding a workable balance of safety and productivity.

Social distancing, cleaning and hygiene practices, the number of staff on the premises at any one time, shift patterns – this is where the list of new considerations begins. What happens in the event that we reach a point where everyone entering the workspace needs to be tested for coronavirus symptoms? Add to this the wider interconnectivity of daily working needs, from customer interactions to managing supply chains, sharing workspaces with other businesses, controlling the flow of people against transport and infrastructure dependencies, and suddenly the ramifications of any changes begin to multiply.

Simulating possible outcomes

With so many possible knock-on effects when implementing the guidelines necessary to control the spread of the virus, finding the optimum work-arounds to continue any semblance of business-as-usual will likely need some experimentation. Experimentation, however, comes with risk.

By eliminating the risks involved in trial and error, simulation lends itself perfectly to adapting to the new world order where COVID-19 remains a threat. This rapid, predictive technology will offer a new level of preparedness.

Process simulation software uses animated, interactive models to replicate the operation of an existing or proposed production system. It enables organisations to analyse system efficiency and safely test process changes to improve throughput and profitability. It is used for evaluating things such as a manufacturing plant layout, setting up or reconfiguring production lines, routing calls through a complex contact centre, optimising staffing resources, or perhaps evaluating the benefits of new Industry 4.0 improvements.

It offers powerful capabilities to positively influence and streamline the continuity of the customer journey and experience. Marginal gains in processes such as systemised warehousing, seasonal stock levels and delivery infrastructure management can all be simulated to achieve greater cumulative advantages in competitive sales environments.

Using a drag and drop interface, you can quickly build a virtual representation of an existing or proposed system, similar to drawing a flowchart. The simulation can then be used to highlight problems, experiment with process changes and run a range of ‘what-if’ scenarios. This allows you to find solutions that will deliver the best results without risk to current production output or capital investment. Decision making confidence will quickly rise as risk factors decrease.

For example, a production line may need to be elongated to allow enough space between stations for safe work practices. Where will this additional space requirement impose and what will be the impact on throughput? Perhaps less storage space, or perhaps it requires other machinery to also be reconfigured. Warehouses, including picking and logistics processes may also need to be restructured.

Simulations can answer questions you didn’t ask and provide solutions you didn’t know you needed. They can teach you how to learn from mistakes you haven’t yet made and optimise processes in ways you never imagined.

Once reconfigured, how about disruptions that will slow down the production process? Equipment will need to be cleaned more frequently, for example. Certain tasks requiring simultaneous input from more than one worker may need to be rearranged, or they may simply take longer than normal. Simulation is more accurate and flexible than traditional process modelling methods, like spreadsheets, as it incorporates the random events and variability that can impact day-to-day factory flow and throughput. This might include equipment downtime in the event that an engineer cannot be reached to resolve a maintenance issue, or perhaps staff absence if an employee is required to self-isolate with immediate effect.

Data-led decision-making

In order to make appropriate decisions around these issues – decisions that will strike the right balance between productivity and safety – organisations need to work with tangible data. But at a time when whole new precedents are being set, past data will have its limitations in informing the decisions of this new world order – and incorrect decisions will pose actual threats to human life. There is little room for trial and error.

This is where digital simulation tools can be truly invaluable. These AI-driven systems learn quickly with cumulative predictive data facilitating a powerful feedback loop.

Digital simulations offer means of testing multiple different possible outcomes quickly, cost-effectively – and crucially, without risk. Questions about staff resourcing, stock controls, waiting times, supply chain management – anything where you can create a flow chart to analyse different outcomes is suitable for digital simulation.

Every business can benefit from testing the viability, sustainability and ultimately profitability of a proposed change or improvement. Typically, modelling occurred after a build, now it’s possible to predict productivity advances and advantages before. Decision making processes are empowered by an improved level of realism and predictability.

Case study

Setting a new throughput target to meet an increase in production demand – when launching a new model car, for example – will require an audit of current lines to see where the daily production rate can be increased. Chrysler did just that, using simulation software to study its line speed when it was tasked with improving one of its plants’ daily production rate from 930 to 969 vehicles.

Reviewing the full production line manually, and then testing different ideas to see the impact of changes on throughput, would have taken time. It would also run the risk of becoming a costly experiment. Instead, by building a digital simulation of the production line, the team at Chrysler were able to remove this risk and discover a quick route to understanding the full picture, testing different scenarios to identify the most effective plan before implementing.

Chrysler’s simulation revealed that two specific stations were causing bottlenecks and slowing throughput. Attention could now be focused on correcting and optimising those stations to speed up the lines without disrupting the rest of the process. The result of this focused optimisation enabled Chrysler to meet its target of producing an extra 39 units per day, which equated to an extra $1million revenue per day. The simulation provided the evidence needed to fast-track this critical decision, in the end with a relatively simple solution.

While this example demonstrates the benefits of proactively optimising production lines under normal circumstances, the elimination of risk, especially where safety is concerned, makes the use of simulation even more vital as a tool to help navigate to more normalised services in a COVID world.

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