Designing a lean storage allocation policy for non-uniform unit loads in a forward-reserve model

Development of an improvement framework for warehouse processes using lean six sigma (DMAIC) approach. A case of third party logistics (3PL) services

This study aims at developing an improvement framework of warehouse processes by improving process cycle efficiency using lean six sigma (DMAIC) approach. A case study method was used to illustrate the evaluation of the existing processes in the warehouse of a third party logistics company with a focus on productivity using warehouse lean tools. Data were collected based on warehouse operational areas of suppliers, customers and internally related with a focus on warehouse core processes. The optimization of the warehouse processes was based on established lean tools. Based on the warehouse evaluation, high non-value added activities were observed leading to a low process cycle efficiency of 40%. After the implementation of the lean six sigma approach, the process cycle efficiency improved of up to 70%. An improvement framework was also established for productivity across the warehouse processes to minimise waste. Lean warehousing has been used to illustrate solutions to a real-time problem of productivity which has negatively impacted on management and customer satisfaction. The study has added to lean warehousing focusing on all the warehouse processes using six sigma DMAIC approach, unlike most literature which concentrates on a specific process. Also develop a framework for the improvement of the processes.

Ramping up a heuristic procedure for storage location assignment problem with precedence constraints

The retail industry is becoming increasingly competitive; as a result, companies are seeking to reduce inefficiencies in their supply chains. One way of increasing the efficiency of operations inside a warehouse is by better allocating products in the available spaces. In this paper, we propose a new heuristic approach to solving the storage location assignment problem (SLAP) considering precedence constraints, in multi-aisle, multi-product picking warehouses. A two-phase heuristic procedure is developed: the products are clustered and assigned to the available spaces. We tested the procedure in the non-perishables warehouse of a real-world Portuguese retail chain, which supplies 191 stores per day. The results show that the new assignment of products allows for an improvement of up to 15% on the distance travelled by the pickers, which implies savings of approximately 477 km per month. This problem is a special case of SLAP since we are dealing with large percentages of non-uniform products. This procedure incorporates four relevant criteria for the allocation decision: the products' similarity, demand and weight, and the distance travelled by the picker. By using a two-phase heuristic method, this study offers companies and academics an alternative and more effective solution for SLAP than the usual methods based on the creation of density zones.

Can collaborative buffering strategies reduce distribution costs while improving product returns?: A case of an Asian e-retailer

Purpose

In order to achieve competitive advantage over the physical marketplace, the e-retailers are insisted on endowing with lenient return policies. The piece-wise returns-and-reordering process incurs excessive buffering and unwanted logistics costs which raises overall fulfillment charges. The objective of this study is to re-design e-retail distribution policy by providing temporal storage at logistics service provides' (LSP) location. The impact of recurrent returns on pricing and profit margins are also investigated over time continuum.

Design/methodology/approach

A framework is developed to reduce the non-value added (NVA) storage and distribution efforts by providing collaborative buffering between LSP and e-retailer. The knapsack based buffering approach is tested and compared with traditional e-retail distribution practices. The revenue sharing concept is mathematically modelled and implemented in GAMS, which finally validated through multiple return scenarios.

Findings

The proposed model outperforms the existing one under all scenarios with different configuration settings of re-ordering, profit margins, and buffer time windows. The distribution cost is found, linearly related to the necessary product buffering space. The findings help to re-design sustainable return policies for individual products so that maximum customer value can be yield with minimum costs.

Research limitations/implications

This study helps to determine the NVA efforts incurred while storing and delivering multi-time returned products to ensure desired service levels. The revenue sharing model provides pricing strategies for e-retail practitioners deciding which product should store in what quantity for how much time at the shipping agency location so that it fulfils the re-ordering at least waiting and sufficient buffering.

Originality/value

The proposed model extends the role of LPSs as temporary buffer providers to reduce returns-and-reordering fulfilment efforts in the e-retail network. This Collaborative framework offers an opportunity to amend the distribution contracts and policies time by time that enhances e-retailer's performance and customer satisfaction.