Home » Manufacturing » What a digital twin can tell you about your warehouse capital plans

Lorcan Sheehan

CEO, PerformanSC

Future capacity plans need to be underpinned by a clear picture of current sourcing and inventory practices and a picture of how existing warehouse, receiving, marshalling and shipping areas are used. 

Leveraging supply chain volume and dimensional data can present a clear picture of actual inventory practices and how existing warehouse and material flow capacity is used. Frequently, this will highlight differences from stated inventory processes, and capacity plans will need to reflect a range of options to support future demand. 

Align forecasts with physical requirements 

Bill of material (BOM) data linked with inventory policies provides insights into future storage needs. These can include ambient, cold, frozen, hazardous and flammable materials — internally and externally. These can be linked to dynamic change as long-range forecasts update and can be updated with supplier or material-specific inventory strategies.   

Flow requirements can also be mapped within a digital twin using current operational timings linked to volume growth. It is important to understand the variability between normal and peak operational requirements.    

Bill of material (BOM) data linked with
inventory policies provides insights
into future storage needs.

Simulate supply chain scenarios 

With a baseline model in place that reflects current operating parameters, the digital twin can support collaborative, data-driven discussions between manufacturing, planning and supply chain teams on the impact of material strategies, VMI operations and insource vs. 3PL. It can also produce a range of capital alternatives for the site.  

The digital model goes beyond simple pallet and storage capacities and includes flow capacity — space, labour and equipment — identifying holistic needs for the site and supporting the evaluation of capital and operational alternatives to resolve them. 

Keeping the model up to date 

Once built, the data-driven capacity model and digital twin can be maintained to reflect operational choices and perform a digital ‘what-if’ in support of future supply chain initiatives. Ideally, the original development of the capacity model should include considerations for data maintenance — BOM and forecast updates, new products and operational improvements — with clear owners and expectations on update frequency. 

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