Minimizing makespan and throughput times at Aalsmeer flower auction

At Bloemenveiling Aalsmeer (VBA), about 19 million flowers have to be distributed daily to customers in a building of 1 million?m2 within a few hours. With the increasing daily number of customer orders, the congestion in the main distribution area increases. As a consequence, the makespan exceeds the available time, and flowers arrive too late at the customers. This paper investigates the concept of zoning in the distribution process, where distributors work in teams for a fixed group of customers in a specific zone of the distribution area. Customers are assigned to zones to balance workload. We show by simulation that this way of organizing the distribution process reduces congestion and leads to considerable improvements in both makespan and transaction lead time

Analysis and Control of Batch Order Picking Processes Considering Picker Blocking

Order picking operations play a critical role in the order fulfillment process of distribution centers (DCs). Picking a batch of orders is often favored when customers’ demands create a large number of small orders, since the traditional single-order picking process results in low utilization of order pickers and significant operational costs. Specifically, batch picking improves order picking performance by consolidating multiple orders in a "batch" to reduce the number of trips and total travel distance required to retrieve the items. As more pickers are added to meet increased demand, order picking performance is likely to decline due to significant picker blocking. However, in batch picking, the process of assigning orders to particular batches allows additional flexibility to reduce picker blocking. This dissertation aims to identify, analyze, and control, or mitigate, picker blocking while batch picking in picker-to-part systems. We first develop a large-scale proximity-batching procedure that can enhance the solution quality of traditional batching models to near-optimality as measured by travel distance. Through simulation studies, picker blocking is quantified. The results illustrate: a) a complex relationship between picker blocking and batch formation; and b) a significant productivity loss due to picker blocking. Based on our analysis, we develop additional analytical and simulation models to investigate the effects of picker blocking in batch picking and to identify the picking, batching, and sorting strategies that reduce congestion. A new batching model (called Indexed order Batching Model (IBM)) is proposed to consider both order proximity and picker blocking to optimize the total order picking time. We also apply the proposed approach to bucket brigade picking systems where hand-off delay as well as picker blocking must be considered. The research offers new insights about picker blocking in batch picking operations, develops batch picking models, and provides complete control procedures for large-scale, dynamic batch picking situations. The twin goals of added flexibility and reduced costs are highlighted throughout the analysis

Enhancing Warehouse Performance by Efficient Order Picking

This thesis studies order picking in warehouses. Order picking, the process of retrieval products from their storage locations to fill customer orders, is regarded as the most critical operation in a warehouse. Using stochastic modelling, we develop a model to estimate order picking system performance on various design alternatives and operating policies. The model is fast, flexible, and sufficiently accurate for practical purposes. The thesis introduces a concept of Dynamic Storage. In a Dynamic Storage System (DSS), orders are picked in batches and only those products needed for the current pick batch are retrieved from a reserve area and are stored in the pick area, just in time. Through analytical and simulation models, we demonstrate a DSS can substantially improve order throughput and reduce labour cost simultaneously over conventional order picking systems, where all the products required during a pick shift are stored in the pick area. The thesis also studies an internal distribution process at a flower auction company. Based on simulation and optimization models, we propose ways to reduce congestion and improve order lead time

Incorporating Worker-Specific Factors in Operations Management Models

To add value, manufacturing and service operations depend on workers to do the job. As a result, the performance of these operations is ultimately dependent on the performance of individual workers. Simultaneously, workers are major stakeholders of the firm. Workers spend a considerable amount of time in their lives at their job and depend on that job to sustain themselves and their families. As a result, firms wishing to satisfy their primary stakeholders should consider workers’ job satisfaction in the design of their operations. Especially given that job satisfaction can promote other positive outcomes for the firm, including lower personnel turnover and accident rates. This thesis addresses the key question of how common operations management decisions may have an impact on a worker’s individual performance and his job satisfaction. In particular, we first provide a literature survey of psychology and ergonomics linking operations decision variables with performance and job satisfaction. Next, we study the effects of assigning goals on performance and work pace regulation. We identified steady work pace regulation patterns associated with challenging goals. Finally, we studied the problem of where to store items in a warehouse such that efficiency (cycl