Data driven analytics applications are especially valuable in production processes with naturally large batch sizes. This is because analytics, in the form of e.g. intelligent scheduling decision engines, aids efficient resource allocation and utilization – directly improving operational results. Naturally, large batch sizes occurs in production processes with naturally economies of scale, i.e. high setup and changeover times and costs. Here are some examples from various industries.

Chemical manufacturing

Many chemical processes involve large batch sizes due to the complexities and costs associated with setting up equipment, ensuring safety, and maintaining quality control. Examples include the production of pharmaceuticals, petrochemicals, and specialty chemicals.

Food and beverage

The food industry often produces products in large batches to meet consumer demand. Examples include baking, brewing, and canning. In these processes, it’s more cost-effective to produce large quantities at once. In the bottling industry, beverages like soft drinks and bottled water are typically produced in large batch sizes to meet demand and reduce the cost per unit.

Pharmaceuticals

Pharmaceutical manufacturing often involves large batch sizes, especially for generic medications. The production of pills, capsules, and tablets, for instance, is usually done in large batches to reduce manufacturing costs.

Automotive, plastics, and electronics manufacturing

In automotive production, various components are manufactured in large batches before assembly. Production processes such as plastic injection molding or vapor deposition based surface treatment processes for e.g. hardening transmissions are examples of processes with high setup times and costs. The production of plastic products, including injection molding and extrusion processes often involves large batch sizes to minimize setup and changeover times.

Electronics components such as microchips and circuit boards are often produced in large batches due to the capital-intensive nature of semiconductor fabrication facilities (fabs).

Textile manufacturing

In the textile industry, fabrics are often produced in large rolls or batches. This is because the setup and maintenance of textile machines can be time-consuming and costly.

Paper, pulp, cement and concrete production

Paper and pulp mills typically produce large batches of paper products due to the large-scale machinery involved in the process.

Cement and concrete are typically produced in large batches due to the size and complexity of the production equipment.

Steel and metal production

Steel and metal production processes, including casting and forging, often use large batch sizes to optimize energy and material usage.

Oil refining

In the petroleum industry, oil refining involves processing crude oil into various products like gasoline, diesel, and lubricants in large batch sizes.

Concluding remarks and related content

Many industries and production processes have large batch sizes, naturally. Large batches reduce setup and changeover costs. Analytics is especially useful in industries with large batch sizes, e.g. in the form of scheduling algorithms for efficient resource allocation and utilization.

The following related articles might also be of interest to you:

• Link: Lot size dependent warehousing costs
• Link: Wire production batch / lot size optimization
• Link: Setup sequencing with Excel Solver
• Link: Changeover sequencing in Python
• Link: Poultry supply chain SimPy library and model

Linnart Felkl

Data scientist focusing on simulation, optimization and modeling in R, SQL, VBA and Python