Our client is a leading manufacturer with 85% market share in their sector in Australia and NZ.
The client was looking to develop a model to help assess manufacturing constraints under different operating and demand scenarios. The model was required at a corporate level to help understand and optimise operational constraints, as well as assisting with the development of business cases for improvement and expansion capex. The key requirements were:
- Ability to calculate demand and throughput down to a site and process level, on a monthly basis
- Allow the business to test the capacity of the existing facilities to handle abnormal demand, and to identify process bottlenecks
- Importation of 18 month forecast base level demand data for each product, by month
- For each demand scenario, and for each process stage, the reporting of total throughput, capacity utilisation, and hours runtime
Parity worked closely with the operations planning team to develop an understanding of the manufacturing processes at each site. This was mapped out in a process flow diagram, which included rated capacities and manufacturing constraints for each process stage. A separate mapping exercise was then applied to the client’s product range to understand the process path and throughput for each. A capacity planning tool was developed using Microsoft Excel, with Power Query used to import demand data from the client’s business system. A scenario planner was developed to allow the client to easily test the impact of abnormal demand, and to mitigate by either shifting production, adding shifts, or investing in additional capacity. The tool was built flexibly to be easily modified for new products or processes. The core output was via a heatmap, which allowed the business to quickly identify bottleneck ‘hotspots’ for various process stages over time.
The capacity management tool provided the operations team with visibility as to potential future capacity issues. The team now has a quick and simple way to:
- Identify periods where demand exceeds capacity
- Re-organise operations to meet this demand
- Plan major capital investment in new machinery as it becomes required
“The core output was via a heatmap, which allowed the business to quickly identify bottleneck ‘hotspots’ for various process stages over time.”
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