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Make sure you’re not caught out by the requirements of a changing landscape
According to a 2020 Material Handling Institute survey, 50 per cent of companies plan to invest $1m-plus in internal supply chain technologies over the next two years. This raises two fundamental issues:
• 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 that spend, so you can meet often volatile customer demand at minimum cost per unit.
Traditionally, the processes a company would take to model the success of these issues would be with static-based systems, such as Excel, or the gut instinct of professionals using best-guess scenarios.
Industry 4.0 has seen businesses move beyond this and embrace digital models focused on connectivity and data analytics – and nowhere is this clearer than with predictive simulation.
This software allows companies to create Digital Twins of their processes, modeling all stages from business functions to manufacturing, offering unprecedented insight. It generates powerful future data and helps demystify much of the analytical process by providing a rich interactive visualization of information.
Being able to test and make assumptions and decisions in a virtual world provides clarity across areas such as capital investments, resource planning, process design, and even service policies.
If you introduce a new product or line into a facility, what’s the impact on internal logistics? Will new congestion points be introduced either outside or inside the facility walls? What are the health and safety implications? Can we get raw materials, components, or finished products to or from the production or assembly areas smoothly?
By creating a Predictive Digital Twin, you can model such new processes and flows, and identify pinch points before they emerge in reality – all in a risk-free, digital facility. For example, Britvic Soft Drinks used our 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 Predictive Digital Twin of the future facility simulated how vehicles would enter the site, flow through parking bays to loading bays, how loading and unloading would work and how the vehicles would then leave the site.
Having made a number of key investment decisions using this virtual site, they then modeled 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 realized how much congestion would occur on certain routes to and from the loading bays, creating both delays and safety issues. Using the Digital Twin, the team identified a safer, optimal solution – including one-way aisles that segregate vehicles whilst maintaining required logistics efficiency.
We’re seeing several trends that have a significant (but often overlooked) impact on material handling. One is the move away from single-use plastics towards more sustainable materials.
Members of the UK Plastics Pact achieved a 30 per cent reduction in so-called ‘problematic plastics’ since 2018, leading to major changes in production processes. Another trend is the rise in consumer bulk-buying during the pandemic – the internal logistics associated with producing a 24-unit pack are very different from that required for a four-unit pack.
In responding to such changes in customer behavior, you don’t want to buy 30 forklifts if you only need 20. Predictive Digital Twins can help you create a water-tight business case for your proposed MHE investments – so you both design and rightsize 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 damaging extra pain and rectification costs due to unexpected bottlenecks and delays.
Demand for automated storage and retrieval systems is accelerating. The global ASRS market is projected to grow by eight per cent by 2025, driven by pressure from just-in time supply chains and technical skills shortages.
Using Predictive Digital Twins 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 save significantly on the CAPEX of the project.
Importantly, Predictive Digital Twins help you understand how something like an ASRS will also affect upstream and downstream processes. We recently helped a major Tier 1 automotive supplier to build a robust business case for ASRS investment.
“We’re seeing several trends that have a significant (but often overlooked) impact on material handling. One is the move away from single-use plastics towards more sustainable materials”
Analysis of the developed Predictive Digital Twin enabled the team to understand the trade-off between the capability of the ASRS and the resulting wider process control logic that they could implement, resulting in a significantly lower cost to serve their end customer. They could then hone in on the ASRS performance needed to enable that buffer level.
Given the complex interplay of dynamic processes within most company’s internal logistics, it can be hard, if not impossible, to fully understand the many knock-on effects of people, processes, or technology 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 Digital Twins 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 de-risked business case.
Oliver Bird is the business development director for Lanner, a data and simulations service provider
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