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Just-in-time
Published in Stuart M. Rosenberg, The Digitalization of the 21st Century Supply Chain, 2020
As a new concept, just-in-time logistics can be defined as the application of the JIT management philosophy to four main components of logistics, including customer services, order processing, inventory management, and transportation management. If the flow of goods and services is well managed, the quality of customer service will increase. Customer service is related to the output of logistics systems and plays a very important role in creating, developing, and maintaining customer loyalty and satisfaction. Order processing includes all the order activities, including collecting, checking, entering, and transmitting order information. It reflects a relationship between suppliers and firms. The order cycle time, that is, the time from when a customer transmits an order to the time the customer receives that order, is very crucial for customer satisfaction. The firms can compress the order cycle time by implementing just-in-time logistics successfully. Inventory management involves managing appropriate inventory levels, which is necessary to serve the demand in a supply chain. It means keeping stock levels as low as possible but at the same time providing the desired level of stock available to serve customers’ demand. That will lead firms to significantly reduce logistics costs. Transportation transfers materials, components, and finished products between raw materials suppliers, distributors, retailers, and end customers in a supply chain.
Customer Service
Published in William C. Copacino, Supply Chain Management, 2019
Surprisingly, the company found that order cycle times averaged more than 12 days. Although it was able to expedite orders to serve some customers in as little as 5 days, the 95th percentile of order-processing lead times was over 32 days, meaning that almost half of the orders were taking from 12 to 32 days to process and deliver to customers. Furthermore, many companies find that the administrative burden required to fully process and close an order can be considerable. For example, one $500 million consumer products company employed more than 150 people for these activities.
Manufacturing support for the Petitto MULE
Published in Y.J. Wang, R. Larry Grayson, Richard L. Sanford, Use of Computers in the Coal Industry, 2020
Customer orders are received by accounting services and forwarded through job costing to customer order processing. Customer order processing, in turn, initiates the manufacture and/or shipping of finished goods. Manufacturing processes as well as the transfer of goods from physical inventory to shipping is managed by the shop floor control unit. Information concerning the shipment of finished goods is forwarded back through shop floor control and customer order processing to accounting services.
An advanced order batching approach for automated sequential auctions with forecasting and postponement
Published in International Journal of Production Research, 2023
Xiang T. R. Kong, Miaohui Zhu, Yu Liu, Kaida Qin, George Q. Huang
First, the combination of re-engineered auction order fulfillment automation process with postponement-based order batching can enable the auction market to realise responsive auction logistics operations and concurrent order processing, compared to the performance of the existing manual system. Second, the buyer order completion rate is introduced in the proposed order postponement rule. In the implementation of the proposed postponement approach, the decision-maker needs to adjust the time interval and the threshold of buyer order completion rate to trade off the total processing time and system response time. Third, the performance of the proposed method is not affected by the number of buyers. The suitable parameters of the order postponement rule (i.e. time interval and threshold of buyer order completion rate) should be chosen to balance total order processing time and system response time.
Scrutinizing IoT applicability in green warehouse inventory management system based on Mamdani fuzzy inference system: a case study of an automotive semiconductors industrial firm
Published in Journal of Industrial and Production Engineering, 2023
Asmae El Jaouhari, EL Mehdi El Bhilat, Jabir Arif
In addition, Figure 4 explains the criteria chosen for every FIS. Beginning with green purchasing (GP), four criteria are selected for the FIS 1: supplier-customer collaboration (SCC), enforcement of stakeholders (ES), quality Regulations (QR), and replenishment (R). The second FIS covers five inputs: Required Quantity (RQ), Green Technology (GR), Green Warehouse Policies (GWP), Green Items Unloading (GIU), Quantitative and qualitative control (QQC), and one output that is Green Item Reception (GIR). As far as FIS 3 is concerned, customer order processing (COP), Green shipping (GS), delivery and returns (DR) and Green receiving inventory (GRI) are applied to determine the Green Order fulfillment (GOF) value. Product Information (PI), green shipping charges (GSC), Customer billing information (CBI), and Delivery Lead time (DLT) are selected for the FIS 4 to calculate Green sales orders (GSO). Finally, FIS 5 involves five inputs, which are Payment Regulation (PR), Project Reports and Communication (PRC), Top-tier knowledge (TTK), service delivery quality (SDQ), and Green Transportation Policies (GTP), to evaluate the green delivery level. In the second phase, FIS 6 is assessed by the outputs of the first phase: GP, GIR, GOF, GSO, and GD to evaluate the GWIM performance as a whole.
Order processing task allocation and scheduling for E-order fulfilment
Published in International Journal of Production Research, 2022
Nan Chen, Wenxuan Kang, Ningxuan Kang, Yongzhi Qi, Hao Hu
The problem introduced above is strongly NP-hard according to Du and Leung (1989) and the MIP model cannot handle the instances with 3 threads and 200+ orders in 3600 seconds of computational time due to large number of binary variables. However, the time limit of the e-order processing is usually no more than 10 minutes for such an online problem at JD.com, one of China's top e-commerce companies with the net revenue of 114.3 billion U.S. dollars (JD.com 2021) for the full year of 2020. The current policy for order processing at the Order Fulfillment Center (OFC) of JD.com, is to place all the orders on the parallel threads directly in chronological order of placement, and then to process them in the queue orders separately. If there is at least one predecessor unfinished, both the order and the assigned thread are blocked until all the precedence constraints on it are released. The pseudo code of the current policy is described in Appendix 1. Therefore, an efficient heuristic policy with high performance to allocate and schedule the orders is quite an urgent need.