CHALLENGE

Companies that pack fresh products face massive complexity and unpredictability. They process many different products, all of which have specific requirements in terms of quality, class and size. They deal with a multitude of packaging requirements and variability in price agreements for each customer. And they handle huge swings in supply and demand. But the time frame in which packers must match supply and demand is short.
How do you balance customer requirements with product and process complexity to achieve high customer satisfaction and high ‘valorisation’? And how do you deal with last minute changes in supply and demand – for example, if a batch is rejected because it does not meet the quality requirements?

APPROACH

The packer had been using Excel spreadsheets to allocate products on packaging lines and carry out detailed line planning. This had caused misunderstandings and mistakes – and a higher workload than necessary for the planners. They were losing time creating iterative plans, and there was uncertainty about which version of the plan was most up-to-date and about which numbers were correct.

We knew that the More Optimal platform would resolve these problems and explained the benefits to our client. The need was so great and the benefits so obvious that the packer did not even want a ‘proof of value’, but immediately decided to develop and implement a dedicated application based on the More Optimal platform.

The goals were (1) to arrive at a workable schedule faster, (2) more efficiency in the operation, (3) shorter lead times relating to product freshness, (4) better demand fulfilment and (5) increased flexibility.

The More Optimal platform makes it possible to build a customer-specific application in a short time with all relevant planning rules built in. The application is set up in close consultation with the user. First, the relevant Key Performance Indicators (KPIs) are defined to quantitatively determine the quality of the allocation plan. Two of these KPIs were demand fulfilment and lead time (related to product freshness).

In a number of joint work sessions, we drew up the allocation rules for products and determined how products from suppliers should be allocated to customers. By working intensively with the packer, we developed a dedicated application that shows the consequences of the decisions made by the planners and gives advice for better planning. This application was further expanded with support from the planners in order to optimise the detailed planning per packaging line to minimise changeover times on the lines and to increase the throughput capacity (OEE) of the lines. The application measures the operational performance based on the agreed KPIs.