A New Approach to Batching: Make a Size

Issues with batching can significantly impact the flow characteristics of a

Issues with batching can significantly impact the flow characteristics of a manufacturing plant. By understanding the underlying principles behind these supply chain issues, it is possible to avoid them and achieve significant benefits for the plant.

In the case of automotive operations, many of the processes involve large batching. The following are some of the commonly found large batching operations in automotive manufacturing units:

• Forging - involving forging presses • Casting - involving core-making and moulding machines • Plastic components - involving plastic moulding machines • Sheet metal - involving metal presses

Problems with large batch production

The conventional approach to maximize productivity in manufacturing plants is to aim for high machine utilization and process batches as large as possible. Large batches reduce non-productive setup times and increase productive processing time, which is incentivized through capacity utilization metrics. Finite capacity scheduling software also creates schedules with larger batches and lower variety. However, this bid to ensure capacity utilization in the supply chain leads to a host of issues in the plant.

Issue 1: One problem with large batches is called ‘capacity stealing’. This occurs when capacity is used to produce items that are not on the critical path, meaning customers do not require them immediately . To form large batches, the planning team may select orders from a wide time horizon, even up to three months, and group them. This can result in the production of items that are not needed immediately , potentially at the expense of required items for confirmed orders or immediate requirements.

Issue 2: When non-critical items are produced to make batches, it results in increasing finished goods (FG) inventory that customers may prefer to avoid picking up ahead of schedule. This blocks working capital and takes up space in the warehouse.

Issue 3: Another problem associated with large batches at batching machines is the creation of ‘capacity waves’ at downstream operations. This occurs when the batching machine feeds multiple specialized manufacturing lines downstream, leading to "lean" and "peak" production periods for these lines. During some periods, some downstream processes experience near-starvation, resulting in idle time for labour. Conversely, during some other periods, downstream processes flood, necessitating overtime and extra payments for labour. (Note: When this happens, a common misperception arises that the batching machines are the constraints to the flow in the plant. However, our experience has shown that these large batching machines generally have excess capacity. The abundance of inventory lying beyond these machines clearly indicates this. The real constraint is often found in downstream operations such as welding and finishing in sheet metal operations or fettling and finishing in castings). Large batch production leads to in increased work in progress, higher finished goods inventory and decreased throughput - consequently, high variable production lead times and poor reliability, resulting in poor on-time delivery to customers. Ultimately, in addition to operational problems, there is customer dissatisfaction.

Problems with small batch production

The downsides of large batch sizes suggest that reducing batch sizes is an ideal solution. However, as mentioned earlier, smaller batches increase the required setups, potentially turning a non-constraint machine into a constraint machine, and reducing productivity and longer lead times. As a result, small batches can also lead to poor on-time delivery performance, leading back to the initial problem.

A solution that is less than ideal

Since there are issues with both large and small batch production, in practice, batch size issues are often treated as a trade-off between capacity utilization and reliability, with companies prioritizing protecting capacity at the beginning of the month by producing larger batches according to the monthly plan. However, as the month progresses, urgent demands from customers, stockouts, or sales teams eager to maintain delivery commitments can cause the plant to break planned batches and increase setups to accommodate these urgencies.

This trade-off is not necessary. Despite these challenges, there is a solution that can ensure both order reliability and capacity utilization.

The steps towards a solution are as follows:

Step 1: Determine the optimal batch size

To balance between machine utilization and on-time delivery performance, it is necessary to avoid both extreme batch sizes (too large or too small) and identify the optimal point for different machines with different capacities. This process involves iterative testing to find the best batch size for each machine.

Step 2: Decouple the batching machines

The first step alone will not bear any fruit. Decoupling the batching machines from downstream operations is crucial to give them the flexibility to operate out of sync with the remaining supply chain operations without disrupting the flow. It can be achieved by introducing a buffer immediately after the batching machines.

Step 3: Implementing a pull-based system

The next step involves implementing a pull-based replenishment system to and from the buffer after the batching machine. This means the downstream processes can request inventory from the buffer as and when needed and consume it for their processes. By doing this, the downstream processes will only receive what they need, reducing the risk of excess inventory and freeing up space in the warehouse. It also means that the batching machine will not push out batches on a fixed schedule. Instead, it will just replenish what has been consumed from the buffer as and when necessary. Overall, a pull-based replenishment system will improve the systems’ ability to respond quickly to changes in demand and increase the reliability and efficiency of the manufacturing process, ensuring that customer demand is met without excessive inventory or expediting requests.

Summary

Implementing these steps may challenging, as this solution goes against intuition. While it is easier to understand local optima, grasping global optima requires systems thinking. Furthermore, performance incentives tied to capacity utilization and local optima figures can pose a challenge. Even if the team logically agrees on the solution, there may be a reluctance to change until they consistently observe that, even without large batches, their capacity utilization incentives are not affected.

However, once the team realizes the solution's benefits, such as increased output (up to 30%) and a high on-time delivery rate (over 95%) achieved by prioritizing flow improvement all along the supply chain, they will likely abandon old habits. The hidden capacity that is unlocked by these steps is a powerful motivator for change.

About the author –

Achal Saran Pande, an MBA from IIM-Indore is a Partner at Vector Consulting Group, a management consulting firm with one of its kind implementation-led solution approach. He specializes in resolving persistent problems in supply chain and operations using systems thinking. Vector has assisted automotive companies, including Tata Motors, Ashok Leyland, Royal Enfield, TVS Motors, Fleetguard Filters, International Tractors, J.K Fenner, and Volvo Eicher, among others.

Disclaimer:

Deccan Herald does not vouch, endorse, or guarantee any of the above content, nor is it liable for any claims arising thereof.

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A New Approach to Batching: Make a Size