During my school days, I visited a dairy plant that produced a limited variety of products with dedicated equipment for each type of product. Availability of dedicated equipment is less prevalent today, especially with facilities that have expanded as demand grew and also expanded the variety of products.
Right from processing raw milk, you could have dedicated or common equipment for pasteurized or unpasteurized milk, equipment with the ability to pack items in different sizes, and equipment that produces and packs cheese, yogurt, butter and other milk products from raw milk.
One of the challenges today at dairy plants is schedule attainment. This metric measures the actual production as a percentage of scheduled production.
Dairies work on demand forecasts to get maximum plant output. Longer batch runs are often planned every day to achieve high levels of resource and capacity utilization.
With customer demand becoming diverse, smaller batches of different products are expected by customers today, with increased frequency of delivery. Smaller batches bring additional operational constraints such as sequencing, cleaning time, etc., that must be accounted for, which is making plant teams change their schedule frequently. Schedule attainment, as a result, is poor in many dairies.
Planning and scheduling in dairy are not simple today and have a direct impact on profitability. Some of the production planning and scheduling challenges in dairy plants include:
- Sequencing batches: A daily production plan is given by a planning team, but raw milk, pasteurization or filling batch sequences are decided by experienced people in the plant who have, over the years, worked on optimizing the output. It is easy to sequence batch runs in one area without having the visibility of upstream or downstream batch sequences, but holistic capacity optimization becomes difficult to do on paper or spreadsheets.
- Changeover constraints: With production batches becoming smaller, cleaning changeovers have become inevitable on a day-to-day basis. Changeovers reduce the availability of the equipment, leading to poor utilization of equipment. Experienced plant teams are very efficient in reducing the number of changeovers, and maintenance teams always use idle times to carry out autonomous maintenance or preventive maintenance. The challenge today is going one step further in identifying opportunities where overall frequency of cleaning changeovers across the plant can be reduced.
- Max time between processes: Many processes, including evaporation, crystallization and homogenization, are dependent on a previous or subsequent process. Only a maximum holding time is allowed between these processes, or else there will be yield losses. So you may have a holding tank, but it can hold the product for only a certain amount of time before it loses its shelf life or eligibility to be processed further. This creates a significant dependency on when a downstream batch must be planned by checking upstream process adherence.
- Tank capacity constraints: Dairy is a capital-intensive business, and many dairy processing facilities have expanded their capacities over time, including tank capacity for holding product between processes. The planning challenge such expansions have created is in arriving at the right batch sizes for movement from raw milk to finished product and ensuring finished products are not lying unsold, capacity is optimally utilized and all the constraints are accounted for.
- Storage space constraints: Production teams — while optimizing equipment utilization, especially for downstream operations — need to keep in mind the space in which they must keep finished products. When you have finished products occupying space, downstream operations will be forced to hold product or plan production at a time when there is space availability. Filling schedules decide what size of cartons or packs are needed to occupy space in the plant. Poor material planning in the packaging area can easily block space, leading to equipment downtime due to material unavailability. If you see downstream operations having poor overall equipment effectiveness, the symptom may be space or material unavailability, but the root problem may lie in production planning.
- Planning also for co-products or by-products: Skim milk further processed can provide raw whey, casein powder or whey powder, or even skim milk powder. The upstream processes of skim milk production, therefore, will have to consider a batch size equivalent to how much skim milk must be produced, as well as how much of these co-products or by-products are to be produced. This makes batch sizing very dynamic, and dynamic changes in the demand of the co-products and by-products can change the planning and scheduling for the dairy.
Production planning and scheduling is a challenge that needs attention if your dairy business is becoming more and more demand-driven. Whether a dairy facility sources milk from its own farms or sources milk from farmers on a need basis, managing the value-addition processes efficiently is key to running a profitable dairy processing facility.