Cost Deployment Analytics
Enabling enterprises to adapt World Class
The Largest FMCG company would like to implement digital program and chosen cost deployment analytics as one of the important use-case to target loss reduction and decrease the conversion cost. Manufacturing Cost deployment was first proposed by Prof. Yamashina and Kubo (2002). The objective of the analytical model is to reduce manufacturing costs. It is a seven-step method to select what improvement projects to implement. This input sources of the data is the shop-floor assets granular asset state, material waste - real-time from the automation systems or setup newly sensor/IOT Gateways to acquire the data and conduct the deep-dive analytics.
Carbynetech conducted assessment of use-case and could quickly draw out the features, user stories and wire frames with the manufacturing experience of similar domain companies. Our engineering services and technology team studied the automation level in one of the model factories and configured OPC software for data acquisition. In few production lines, leveraged the existing SCADA and PLC sources and for the waste and rejection count/flow/load sensors are installed. The IOT platform used in this use-case was Splunk IOT, but we can use Azure or AWS too.
The solution covered the below modules.
There was an immediate improvement in asset performance, real- time visibility of cost deployment analytics in which they could benchmark with similar categories and factories. It also resulted in significant cost savings, and enabled manufacturing - WCM group to set the new standards of asset performance.
WE DID THIS FOR THEM.
WE CAN DO IT FOR YOU
Find out more about how you can use IOT for manufacturing and target for zero losses and waste.