With unprecedented decision intelligence capable of helping a business navigate uncertain times, one of the most valuable modern technologies for any enterprise is a Prescriptive Simulation Twin.
As with any technology, though, choosing the right Prescriptive Simulation Twins from the myriad of options can be a difficult process. Expectations are higher than ever, and users demand greater security, faster and more flexible configurations, customizations that mold the digital twin to their specific needs, and a smooth user experience. Digital twin customers want a tool that is cost-effective, seamlessly integrated with existing systems, and compatible with a modern technological stack. They want efficient, low-cost support, reliable performance, and complete trust in the simulation outcome.
Finding a Prescriptive Simulation Twin that meets all these criteria is a challenge but there are at least six must-have features that should be considered essential for every simulation web application.
A Digital Twin Visualization Component feature provides a high-fidelity digital replica of the entire simulated system or a specific dataset. This enables a user to develop a realistic and exhaustive Prescriptive Simulation Twin of an entire production system, simulate its complete operational model and include multiple production sites and complex flows (factories, stocks, transport options and more).
This feature offers the unique ability to replicate all activity and interaction throughout a production chain, regardless of the number and location of manufacturing sites, suppliers, contractors, and subcontractors involved.
Imagine a Production Line Manager. Whether defining a production planning strategy for the months ahead, optimizing production for uncertain demand, or seeking to anticipate bottlenecks, the Production Line Manager requires visibility on the end-to-end operations and the cascading effects of different decisions across the entire line.
A Prescriptive Simulation Twin allows that Manager to create and run unlimited “what-if” scenarios that simulate the outcome of these various strategies. By including all necessary data (including demand, contractor’s agreements, production output), the Production Line Manager can model real-world constraints (including production capacity, labor shifts, lead times) and test several “what-if” scenarios for pre-selected KPIs (e.g., revenue, profit, service level, CO2 emissions).
Thanks to the Prescriptive Simulation Twin, the Production Line Manager receives a comparative analysis of all these alternative scenarios to help determine the most effective strategy in relation to different decision criteria.
The increasingly unpredictable future not only makes decision-making complicated and often the objectives business managers are given are contradictory. For example, a decision-maker might be told to simultaneously cut costs but also increase productivity. It is a challenge to meet these contradictory goals as well and develop resiliency in the face of uncertainty.
Consider that Production Line Manager who needs to significantly boost the performance of the line to meet increased demand without altering manufacturing capacity. Despite competing goals, by running “how-to’ prescriptive optimizations, the Production Line Manager can determine the optimal course of action as well as generate a step-by-step implementation.
Bottleneck identification gives a user the ability to automatically identify bottlenecks and operational issues at each step of the production line before they impact their business.
By gaining a deep understanding of the actions to take, when and where to focus leverage, business managers can quickly react to unexpected events, minimize production downtime, identify crucial points of operational efficiency, define contingency plans, thus ensuring maximized production capacity and improving delivery performance.
Business managers are tasked with answering key questions such as “How risky this scenario is?” and “How confident am I about my simulated scenario result and recommended plan?”.
Uncertainty analysis enables that manager to establish the extent to which uncertainties or variability in the input data, or the simulation model itself, can affect the simulation results. Moreover, it measures the accuracy of the simulated data (determined by the number of simulations executed on a specific model) and provides a confidence interval for the simulated KPIs.
A simulated dataset can have a certain level of variability without changing much about the KPIs or, on the contrary, it can have a lot of impact on the simulated results. When the stakes of decision-making are high, advanced features such as sensitivity analysis, help decision-makers determine on which action levers they should focus first by identifying the parameters that have the most impact on their KPIs.
For example, in the case of a forecasted demand that must meet multiple objectives such as profit, service levels and the environmental impact, the sensitivity analysis could weigh the influence of the predicted demand, the number of spare-parts necessary in the production process, the transport distance, and determine which of these has the most impact on the key KPIs.
Available on the Cosmo Tech AI-Simulation Platform and supported by the most advanced features, the Web Application has been built to impart a high-quality user experience. Essential features include pre-built charts for easy visualization and interpretation of analytics, as well as an overall clean design to provide users with a rich yet intuitive experience. All of this results in a powerful and operational web application to start mastering simulation like a pro, and working on your business goals in the most efficient and convenient manner, whether as a Production Line Manager, a Maintenance Manager, or a C-level Executive.
In today’s complex and uncertain times that call the resilience of any value chain into question, industries require an end-to-end operational visibility and the right methods to react fast. While a user might benefit tremendously from using a simulation platform, the simulation end user-experience is what will make the difference in achieving unparalleled decision-making to ultimately predict a profitable and a sustainable future, ensure user adoption and digital transformation across the entire organization.
Through the strategic use of simulation, highly scalable architecture and customizable user-friendly web applications, Cosmo Tech provides an innovative approach to simulate and optimize entire operational systems. This results in immediate, measurable benefits for the organization and next-quarter value creation.
