Smart Trolley Apps: A Solution To Reduce Picking Error

An order picking activities refers to an act of retrieving any items from the storage locations in the warehouses. In common situation, these activities is often performed by human. Due to that condition, high human error and high cost impact were spotted on a manual order picking activities. Thus, previous studies have developed various methods to support the practitioners especially in creating a more efficient order picking process. In spite of the vast discussion and evidence that shows an order pickers tend to deviate from its optimal routes and putting the efficiency of these routing approaches at stake, very little discussion were focus on the implementation of smart application through IT usage and device to reduce the problem faced in the warehouse. Thus, it is the main intention of this this paper to presents a detailed analysis on the relative factors affecting the efficiency of order picking activities in the warehouse and suggest the smart trolley as a solution to overcome the problem. The smart trolley apps is then proposed to increase the picking process in warehouse. The results of this paper indicate that extensive use of smart trolley apps as a solution to a more effective ways of order picking

A Model for the Rapid Distribution of Critical Medical Countermeasures to Large U.S. Populations During a Public Health Emergency via the SNS-RSS-POD System

In the event of a large scale public health emergency in the United States, the need for emergency medical supplies may quickly exceed existing local and regional resources. In these circumstances, specific life-saving countermeasures may be released from the CDC (The United States Centers for Disease Control and Prevention) Strategic National Stockpile (SNS) and delivered to local Points of Dispensing (PODs) via a rapid emergency distribution system that involves multiple governmental agencies and private sector organizations. Included in this distribution system are temporary Receiving, Staging, Storage (RSS) warehousing operations. One of the primary objectives of this SNS-RSS-POD system is to treat the last person in need in the last active POD within 48 hours of the decision to activate this system. There is a concern that under certain conditions, some PODs may not have sufficient service (treatment) time to meet this 48 hour objective. This study explores this concern and focuses on increasing the amount of available service time for the last active POD (and the other PODs) by reducing process times elsewhere in the system. A model is presented for designers and operators of these systems to assess their system; predict which POD is expected to be the last active POD; and estimate the amount of available service time for that last active POD. Further, utilizing Critical Path Methods (CPM), opportunities for process improvements are examined and recommendations are offered. A supporting mathematical model is developed that represents the SNS-RSS-POD system in terms of overall system time as well as time spent in individual subsections of this system. Recommended improvements are introduced into this mathematical model to assess the potential impact of implementing these changes. Finally, another supporting mathematical model is developed that expresses the potential impact of these recommended improvements in terms of human lives saved during a public health emergency under certain conditions in which the overall capability of the SNS-RSS-POD system is challenged

Improving the Multi-Brand Channel Distribution of a Fashion Retailer

One has seen exponential growth in the number of clients and in the quantities ordered in the fashion retailing multi-brand channel. It has, therefore, become essential to improve the channel’s distribution process in order to meet the customers’ orders in the shortest time, and in a cost-effective manner, thus complying with the delivery terms agreed upon with the market. To this end, one studied aspects such as the mapping of the supply flow process, the occupation of space and the spaghetti-dash diagram of four current distribution process activities. Besides these, one also analyzed the calculation of productivity, cycle times, takt time, as well as the service level designed, with the purpose of preparing a system to evaluate company performance. In addition to these studies, one resorted to the ABC and SWOT customers’ analyses in order to develop the improvement proposal, which was characterized by: (a) changes in the layout, (b) improvements in the supply flow, (c) implementation of gravity carriers, as well as more ergonomic forms of transport, and (d) the use of computer applications developed in Visual Basic language for the distribution process. Based on this proposal, one succeeded in increasing the amount sorted out by the distributor in an eight-hour shift to 294 articles (11,23%). Cycle time was reduced from 0,015 minutes/article to 0,013 minutes/article (13,33%), which allows for the segregation of articles in time for the next collections. In addition, the occupied space was reduced to 47 m2 on average per collection (1,39%), which is translated into a reduction of 1 498 468 meters (23,34%) in the average distance covered per collection. Furthermore, the number of workers was reduced, on average, by five employees (12,82%) per collection. The storage capacity of the finished product was also increased by 535 boxes (11,30%). The total investment needed to achieve these changes is established as being 23 754,42 €; yet, the payback time involved will only be six months, resulting in a cumulative profit of 84 504,23 € by the end of the fall/winter 2020 collection.info:eu-repo/semantics/publishedVersio

The Impact of Extended Warehouse Management System Implementation on Warehouse Operational Performance: A Case Study of Fast Moving Consumer Goods Industry

Warehouses operating in the Fast-moving consumer goods (FMCG) industry are affected by the supply chain disruptions. Therefore, it is critical to develop faster and effective mechanisms of managing warehouse operational performance. In this regard, this paper aims to evaluate the impact of Extended Warehouse Management System (EWMS) implementation on warehouse operational performance. It intended to achieve two objectives: to examine the advanced features of EWMS and the impact of EWMS implementation on warehouse operational performance. The case study method gathered operational quantitative and qualitative data from multiple sources, ensuring data richness. Descriptive statistics and mean comparison tests through hypothesis testing were used as quantitative data analysis techniques, using the IBM SPSS Statistics 21 statistical analysis software package. The Framework Approach was used to analyse qualitative data. By mapping Process Flowcharts before and after the implementation, the improvements and drawbacks were identified with their root causes. Advanced features of EWMSs are presented by reviewing the literature. The study's findings reveal that implementation of EWMS increases the throughput, average receiving rate, average allocation and picking rate, average loading rate, average last truck dispatch time, and average on-time delivery. The scope of the research is limited to evaluating the EWMS implementation impact on warehouse operational performance in a selected FMCG warehouse. Future researchers can focus on the effects of EWMS on supply chain capability enhancements and the strategic performance of supply chain partners. The in-depth analysis of performance improvements in the extent of the throughput, average receiving rate, average allocation and picking rate, average loading rate, average last truck dispatch time, and average on-time delivery signals warehouse managers in decision making on effective utilisation EWMS implementation. This paper is among the very few evaluating Extended WMS, specifically, empirical investigation of the impact of EWMS system implementation on FMCG warehouse operational performance. Keywords: Extended Warehouse Management Systems, Advance Features, FMCG Warehouses, Warehouse Operational Performanc