Sequential zone picking is an order picking method designed to enhance warehouse efficiency by dividing the storage area into multiple zones and picking items in a sequential order across these zones. Picked items are often placed in dedicated totes and transported between zones using a conveyor system, which manages the picking flow but can occasionally result in inefficiencies during the process. This study presents a variant of the sequential zone picking system, called a dual-lane zone picking system (DZP), which consists of two parallel conveyor lanes without buffers between consecutive zones. This conveyor configuration allows the picker in each zone to alternate processing between the two lanes, thereby lessening the constraints of tote transitions between zones and improving both system throughput and picker utilization. We design and conduct a series of experiments using a discrete-event simulation model to evaluate the performance of DZPs. The experiment results indicate that DZP surpasses the original single-lane zone picking system by shortening the system’s mean flow time in low flow intensity scenarios and achieving a higher maximum throughput and worker utilization in high flow intensity scenarios. Additionally, we investigate the effects of the number of zones and order batching size on the performance of DZP to gain further insights into the system’s operational control.

Determining the number of operators who set up the machines in a human-machine system is crucial for maximizing the benefits of automated production machines. A man-machine chart is an effective tool for identifying bottlenecks, improving process efficiency, and determining the optimal number of machines per operator. However, traditional man-machine charts are lacking in accounting for idle times, such as interruptions caused by other material handling equipment. We present an adjusted man-machine chart that determines the number of machines per operator, incorporating idleness as a penalty term. The adjusted man-machine chart efficiently deploys and schedules operators for the hole machining process to enhance productivity, where operators have various idle times, such as break times and waiting times by forklifts or trailers. Further, we conduct a simulation validation of traditional and proposed charts under various operational environments of operators’ fixed and flexible break times. The simulation results indicate that the adjusted man-machine chart is better suited for real-world work environments and significantly improves productivity.

In an automotive plant, an automated storage and retrieval system (ASRS) synchronizes material handling flows from a part production line to an auto-assembly line. The part production line transfers parts on small-/large-sized pallets. The products on pallets are temporarily stored on the ASRS, and the ASRS retrieves the products upon request from the auto-assembly line. Each ASRS aisle is equipped with narrow-/wide-width racks for two pallet sizes. An ASRS aisle with narrow-/wide-width racks improves both storage space utilization and crane utilization while requiring delicate ASRS aisle design, i.e., the locations of the narrow-/wide-width racks in an ASRS aisle, and proper operation policies affect the ASRS performance over demand fluctuations. We focus on operation policies involving a common storage zone using wide-width racks for two pallet sizes and a storage-retrieval job-change for a crane based on assembly-line batch size. We model a discrete-event simulation model and conduct extensive experiments to evaluate operation policies. The simulation results address the best ASRS aisle design and suggest the most effective operation policies for the aisle design.