Internal supply chains: Where to focus tech investment
There are 2 fundamental issues to consider when looking at internal supply chain technologies:
- Identifying the right type and level of investment to achieve the operational performance and efficiency you’re aiming for
- Deciding the best way to allocate spend, so you can meet often volatile customer demand at minimum cost per unit
With predictive simulation, you can address both these issues – and make evidence-based technology investment decisions encompassing all elements of the internal supply chain from process/product flow and automation to material handling and inventory/storage requirements.
In this article, we’ll look at how predictive simulation helps you plan investments based on evidence rather than instinct.
Assessing the impact of a major process change on WIP, traffic flows and routing
What’s the internal logistics impact of introducing a new product or line into a facility? Will new congestion points be introduced, either outside or inside the facility? What are the health and safety implications? Can you get raw materials, components or finished products to or from the production or assembly areas smoothly?
Using predictive simulation, you can model new processes and flows and identify pinch points before they emerge in reality – all in a risk-free, digital version of your facility. For example, Britvic Soft Drinks used Twinn WITNESS predictive simulation software to understand how a new high-speed bottling line would affect internal site logistics.
First, the team looked at the potential implications outside of the site. The modelled ‘virtual facility of the future’ simulated how:
- Vehicles would enter the site and flow through parking bays to loading bays
- Loading and unloading would work
- Vehicles would leave the site
Having made a number of key investment decisions using this virtual facility, they then modelled the internal logistics movements – including forklift flows bringing raw materials to the line, taking finished product to warehousing and transporting full pallets to loading bays for loading onto empty vehicles.
Until reviewing the simulation, Britvic hadn’t realised how much congestion would occur on certain routes to and from the loading bays, creating both delays and safety issues. By testing solutions in the model, the team identified a safer, optimal solution – including one-way aisles that segregate vehicles while maintaining required logistics efficiency.
As Neil Brinkman, Operations Optimisation Manager, said: ‘We wouldn't have thought about having a one-way system if we hadn't done the simulation. It’s a great way to bring things to life.’
Optimising material handling
Predictive simulation can help you create a water-tight business case for your proposed investments – so you both design and right-size the fleet to handle materials and products at the right pace and at the lowest cost. If you don’t model future scenarios to understand the potential impact, you might well find yourself investing in the wrong equipment or processes, not to mention incurring extra pain and rectification costs due to unexpected bottlenecks or delays.
Integrating automated storage and retrieval systems
Demand for automated storage and retrieval systems (ASRS) is accelerating, with projected annual growth of 7.94% between 2023 and 2029.
Using predictive simulation can help you make more informed decisions about both the ASRS investment itself and how best to incorporate it into your facility and business process. For example, how big should the ASRS be? What performance level do you actually need to meet requirements without causing bottlenecks? If you could validate that your processes can cope with 30-second retrieval instead of 20-second retrieval, you could achieve significant savings on CapEx.
Importantly, predictive simulation also helps you understand how something like an ASRS will affect upstream and downstream processes. For example, we helped a major Tier 1 automotive supplier build a robust business case for ASRS investment. In addition to modelling the specific capabilities of the ASRS, the project team could see the broader impacts of the investment on overall process capability. Analysis of the predictive simulation enabled the team to understand the trade-off between ASRS capabilities and the resulting wider process control logic they could implement, resulting in a significant lower cost to serve their end customer. They could then home in on the ASRS performance needed to enable that buffer level.
Plan and invest based on evidence, not instinct
Given the complex interplay of dynamic processes within most companies’ internal logistics, it can be hard to fully understand the many knock-on effects of technology (and associated people and process) changes. And you don’t want to be caught out post-implementation – be it through unexpectedly poor end-to-end KPI impact, hidden or new bottlenecks, damaging product delays or costly non-value-adding logistical issues.
Predictive simulation help you pre-empt problems and pitfalls, giving you an end-to-end view of the dynamic interactions within your internal supply chain. That way, you can make informed planning and investment decisions, fully confident in a sound and de-risked business case.
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