Many small and medium-sized manufacturing companies process various product types to respond different customer orders in a single production line. To improve their productivity, they often apply batch processing while considering various product types, constraints on batch sizes and setups, and due date of each order. This study introduces a batch scheduling heuristic for a production line with multiple product types and different due dates of each order. As the process times vary due to the different batch sizes and product types, a recursive equation is developed based on a flow line model to obtain the upper bound on the completion times with less computational complexity than full computation. The batch scheduling algorithm combines and schedules the orders with same product types into a batch to improve productivity, but within the constraints to match the due dates of the orders. The algorithm incorporates simple and intuitive principles for the purpose of being applied to small and medium companies. To test the algorithm, two case studies are introduced; a high pressure coolant (HPC) manufacturing line and a press process at a plate-type heat exchanger manufacturer. From the case studies, the developed algorithm provides significant improvements in setup frequency and thus convenience of workers and productivity, without violating due dates of each order.

This paper deals with the problem of batching and scheduling of jobs whose processing times are different respectively. But, they are given as not the exact value but the range from the lower limits to the upper, which makes it possible to group jobs into

This paper deals with the problem of batching and scheduling of jobs whose processing times are given as the duration from the lower limits to the upper, which makes it possible to group jobs into batches. The grouping of jobs is desirable because of the capability of the batch processor to accommodate several jobs at once. The time required to process the jobs in any batch depends on their lower limit processing times. Once processing is initiated on a batch processor, the batch cannot be interrupted, nor can other jobs be started. And all jobs are assumed to be simultaneously available. This paper develops the model to describe these situation and a heuristic method to minimize its total tardiness.