Our expertise in simulation modelling can make a difference to your operations
Posted on 23rd November 2020 at 16:31
Explore the benefits of event-based and agent-based simulation modelling and quickly respond even when unexpected scenarios like COVID-19 happen. There is no doubt companies are under pressure to better perform and continuously adapt and we can help you yield significant savings.
Many companies face challenges with regards to enhancing customer service, reducing transportation costs and continuously improving their processes. A high-level and more holistic perspective on your logistics operations with the use of simulation modelling can yield significant savings for your business.
We, at UK-Centric Supply Chains at Aston University, specialise in event-based and agent-based simulation modelling which could help manufacturing and logistics companies assess their performance, improve the efficiency of their operations and use "what-if" scenarios for production and machinery planning. Also, our expertise in simulation modelling could help companies improve the utilisation of their resources and reduce unnecessary spending when delivering a service of excellent quality.
Leveraging simulation modelling to make a difference to your business
Through simulation modelling and multi-criteria analysis you can develop a better understanding of the complexity of your operations and build new, innovative designs to optimise the product deliver and increase customer satisfaction. Use this methodology to:
map your actual logistics system and represent all operations taking place;
achieve high accuracy by modelling the individual entities and their interactions in detail from the bottom up;
run the analysis and identify performance gaps and/or inefficiencies;
develop alternative scenarios to explore your system’s behaviour and performance in different settings, especially unexpected scenarios like COVID-19;
optimise your operations by reducing unnecessary activities and costs;
evaluate “what-if” scenarios to make quick decisions during disruptions.
Tagged as: Decision-making during disruptions, Efficiency improvements, Optimisation, Simulation modelling
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