Toward resilient and adaptive warehousing with fuzzy-based selection of automated storage systems for industry 5.0

An automated storage system (ASS) is a computer-controlled warehousing system that is used to manage and automatically pick and place parts/goods. A good automated storage system can maximise space and shorten shipments’ response time, thereby helping the company to adapt quickly to an ever-changing market. For many enterprises there is also an urgent need to establish and install ASS. However, many companies find it difficult to design and install the right ASS. Many considerations need to be examined in choosing a suitable ASS, given their various capacities and capabilities. This study aimed to employ the UNISON framework to present a comprehensive model for selecting the most suitable ASS. It identified two fundamental objectives in the ASS selection process: (1) choosing the most suitable design for ASS; (2) choosing the most competent vendor to build and implement the ASS. This study then broke the fundamental objectives down into more detailed mean objectives and attributes. After defining the mean objectives and attributes, the study created a key performance indicator to assess the selection process. An empirical study was conducted among small and medium-sized enterprises (SME) in Taiwan to validate the proposed framework. A qualitative study was then developed by interviewing three related stakeholders — the vice president, the head of the production department, and the senior engineer — to support the identification process in selecting and implementing the ASS. From this case study, we found that our ASS selection model showed good practical viability. Keywords UNISON Framework, Automatic Storage System, Decision Model, Hierarchy Objectives

Purpose- In this study, it was aimed to select the appropriate storage rack system for e-commerce clothing industry, by comparing storage rack systems in terms of criteria such as cost, volume utilization, height utilization, ease of order picking and stock cycle speed. Methodology- First of all a literature review is carried out. Secondly, the comparison of the storage systems is made and the ones that are suitable for the e-commerce sector and that will be included in the AHP (Analytical Hierarchy Process) analysis are determined. Finally, a semistructured interview is done with 3 e-commerce sector representatives and the AHP method is used to analyze the data. Findings- Considering the usage areas, features, advantages and disadvantages; it was decided to include Back-to-Back and Narrow Aisle and Automatic Storage Systems in the AHP analysis. Back-to-Back Rack System was found to be first with 36.2% ratio. Automatic Storage Systems are in the second place due to their cost disadvantage although they are advantageous for all other criteria. Narrow Aisle Rack System is in the third place, although it more cost-effective than the Automatic Storage Systems, it falls behind it in terms of other criteria, especially the inventory cycle speed criterion. Conclusion- As a result of the study using AHP multi-criteria decision-making method, Back-to-Back Rack System was evaluated as the most suitable storage rack system for e-commerce clothing sector.

Conventional simulators have focused on the abstract aspects of an automatic storage and retrieval system, which mainly deals with design verification, alternative comparison, and system diagnosis. Although such simulators can provide overall system visibility by monitoring how well the process works, the simulation models are not sufficiently realistic for detailed design and implementation purposes. To address this problem, we propose a method of control level simulation of an automatic storage and retrieval system in an automobile plant. The proposed method involves four major steps: (1) designing the process and layout for effective storage and retrieval; (2) abstract simulation of the automatic storage and retrieval system; (3) preparing the mechanical design to obtain three-dimensional kinematic models and the electrical design to produce a control program and a plant model; and (4) control level simulation of the automatic storage and retrieval system, including both manual mode and automode simulations via a human–machine interface. The major benefit of the proposed method is the reduction of the construction time and effort required to validate the programmable logic controller program of a real automatic storage and retrieval system, since potential errors can be detected and fixed before actual implementation.

The automated storage system effectively reduces storage costs, making it a key management strategy adopted by various companies. High-density automated storage systems are more complex, and optimizing the system's efficiency by minimizing the number of raw material box (RMB) movements has been proven to be an NP-hard problem. In a robot-based compact storage and retrieval system (RCSRS), RMBs are neatly stored in vertical stacks. Automatic guided vehicles (AGVs) move along the top of the storage system and retrieve RMBs vertically. Besides retrieving the target box, AGVs must also reorganize obstructing boxes stacked above it. As a result, RCSRS requires substantial RMB reorganization, which accounts for a large portion of storage operation time. To address the AGVs box reorganization path planning problem in AutoStore, a high-density robotic storage system, this study formulates a mathematical model to optimize the AGV's reorganization path. Given the number and locations of target boxes, the model aims to minimize the total operating time for AGVs during block reshuffling in AutoStore. Additionally, a heuristic algorithm is developed to optimize the complete order processing workflow, reducing AutoStore's overall operational time and improving system efficiency.

This paper presents a belt-conveyor based parallel storage system (PSS). Compared with the conventional AS/RS, it has advantages including more efficient utilisation of storage space, and faster storage and retrieval of products. The PSS consists of three components: the automated retrieval system (ARS), the automated storage system (ASS) and the compact storage rack (CSR). In the ARS, a vertical screw conveyor is used to facilitate the vertical movement of the unit loads, while a powered belt-conveyor is used for the horizontal dimension. Additionally, a powered conveyor system enables motion along the depth dimension, meaning each lane in the CSR is connected to several storage cells. Horizontal belt-conveyor and powered conveyor in the lane constitute cross-belt which causes the parallel process. On the other side of the rack, a unit load lift, a RGV lift, several rail-guided vehicles and a buffer rack constitute the ASS. Based on the system, we formulate separate travel-time models for ARS and ASS, under the assumption of randomised, uniformly distributed storage rack positions. Computer simulation with Matlab is used to validate the models, and optimise the automated storage system.

Selecting the appropriate type of capital-intensive storage systems is an important decision for warehouse managers. However, such a decision is complex due to various available storage systems. In addition, warehouse requirements such as storage capacity and throughput influence this decision. This research provides insights that enable managers to select the suitable type of storage system which minimizes the investment and operational costs while the warehouse design requirements, in particular the storage capacity and throughput, are met. To obtain these insights, an Excel®-based decision support system is developed for a set of most common types of manual and crane-based automated storage systems in pallet and case warehouses. The decision support system uses the closed-form formulas from the warehousing literature and also Monte Carlo simulation to approximate the travel time in each storage system. The results show that the choice of automated or manual storage system and the associated costs depend on the required capacity and throughput. When the storage capacity and throughput are low, the manual pallet racks are the preferred storage system and incur the lowest costs. As the storage capacity and throughput increase, there is a need for more compact storage systems that can store more loads in a smaller footprint. Thus, for medium to high capacity levels, double-deep automated storage systems and deep-lane compact storage systems are the ones with the lowest investment and operational costs. The results for the case warehouses show that the investment and operational costs increase rapidly with an increase of the throughput. In particular, the increase is noticeable for operational costs of the shelf rack system and the investment cost of the miniload system where the storage capacity and throughput level are high.

The Materials Distribution Center (MDC) at IBM Endicott, New York, is a new automated warehousing facility (Figure 1). In addition to the conventional facilities, the warehouse contains an Automatic Storage and Retrieval System (Stacker Cranes), a network of pallet conveyors, and an IBM 1800 Data Acquisition and Control System to control the Automatic Storage and Retrieval System and portions of the conveyors. The warehouse, adjacent to the main manufacturing buildings, is for storage of raw materials, parts, and assemblies.

Biobank is the key element in translational medicine and precision medicine. The automatic storage system of biobank can guarantee the quality of sample and make operationconvenient, storage efficient, and running cost economic. It is widely applied in the world. The first automatic biobank in China has been established in December 2016 in Shanghai Changzheng Hospital. and is used on managing overall process of sample storage. It can also reliably record complete sample-related electronic information through seamless connect with hospital information system (HIS). Automatic storage system will become the priority-choice of biobank construction. More and more biobank willtransform from manual storage into automatic storage. Key words: Biobank; Automatis strorage; Managemet

Modern automated warehouses are equipped with one or many expensive and sophisticated equipment, such as palletizing robots, automated guided vehicles as well as an automated storage and retrieval system (AS/RS). These equipment are operated manually at many levels. These manual interruptions are accompanied by disadvantages of slow storage and retrieval speed, high operating costs and high frequency of errors in the operations. This paper presents an approach for efficient robotic stowing of items for inventory replenishment in a storage system. The objective is to enable a robotic arm system to stow items into a storage bin system and automatically generate a file to indicate which bin each object is stowed to. This would require a robust object recognition imbued with recognition history such that a previously recognized object is remembered as being stowed, even if it has been obscured by other objects subsequently during the task. A feature confidence aggregation strategy has been implemented to analyze a sequence of images containing a number of objects that are added to the storage system sequentially. The strategy is based on a weighted aggregation of ranked machine-learned classification scores and feature-matching recognition scores. This method is able to produce a high recognition rate and has been applied in the Amazon Robotic Challenge 2017 by Team Nanyang.

The control of biofilm formation by hydrodynamics of purified water in industrial distribution system

In this paper the authors attempt to modify the Brown Gibson Plant location model to consider the objective factors and applied analytic hierarchical process to consider the subjective factors in the decision process of selecting automatic storage and retrieval systems in place of traditional storage systems.

India is one of the largest producers of food grains in the world. The country has a diverse agricultural sector that produces a wide range of crops, including rice, wheat, maize, pulses (such as lentils and chickpeas), and oilseeds. Rice and wheat are considered essential for ensuring food security in India. India has an extensive network of food grain storage infrastructure to cater to its significant agricultural production. The storage infrastructure in India is primarily managed by the Food Corporation of India (FCI), state government agencies, and private sector entities. Some of food grain storage infrastructure in India are warehouses, covered storage structures (silos), mandi storage facilities (temporarily store grains) and strategic reserve (buffer stock for food security). Private sector entities are increasingly investing in the modern storage facilities including temperature-controlled warehouses and automated storage systems, to improve storage capacity and reduce post-harvest losses. India faces challenges in effectively managing and maintaining the quality of stored food grains. Issues such as inadequate storage capacity, insufficient maintenance, lack of proper pest control measures, and logistical constraints contribute to post-harvest losses. The government and other stakeholders are continuously working on improving storage infrastructure and implementing technological solutions to address these challenges that tiggers for spoilage, mold growth, insect infestation and excessive drying. The real time monitoring and controlling of these factor during the storage period is a cumbersome task and needs advanced techniques. In this aspect Internet of Things (IoT) offers numerous benefits to food grain storage systems including real-time monitoring, early warning systems, optimal environmental conditioning, energy efficiency, inventory management, traceability and predictive analytics. By leveraging IoT technology, the industry can improve storage practices, reduce losses, ensure food safety, and enhance the overall efficiency of grain storage operations.

With the development of modern logistics, the traditional storage system doesn't meet the development needs of the industry due to low efficiency. This paper presents a solution to integrate the modern new technology into the automatic three-dimensional storage system. The electromechanical transmission and control system is designed, which is mainly composed of three-dimensional warehouse, stacker, industrial robot, automated guided vehicle (AGV), programmable logic controller (PLC), and so on. The simulation and test are carried, and the result shows that the system can automatically complete the packing pallet, intelligent transportation and automatic storage with the advantages of high volume utilization rate, high efficiency and high precision, which can better adapt to the production and operation needs of modern automated factories and logistics industry.

An automatic disc storage system transfers discs automatically to storage or an optical disc drive using a robotic arm. For example, an optical archive system uses an automatic disc storage system to efficiently handle a large number of discs. The automatic disc storage system commonly uses a multi-bent leaf spring (MBLS) to insert and hold a disc. In the automatic disc storage system, incomplete insertion of the disc can occur if the disc is not moved properly into storage by the robotic arm. Incomplete insertion causes several problems and therefore should be analyzed carefully. This paper examines the dynamic response of the disc during insertion. Using Castigliano’s second theorem, we analyzed the relationship between deformation and the applied forces of the MBLS at the moving contact position between the MBLS and disc. The formula used to describe this relationship also provided the corresponding design parameters of the MBLS. Disc displacement was determined using a one-factor comparative design in transient analysis. An objective function was defined as a distance of the disc to ensure complete disc insertion. The number of variables was reduced based on the objective function. Interaction among variables was investigated in a 32-full-factorial design. For the MBLS design to prevent incomplete insertion, the objective function increased by 140.4%.

According to the AS/RS (Automated Storage and Retrieval System) characteristics of a company, we analyzed and defined the basic data and basic logical relationships of the system. Through some abstract and reasonable simplification, application of Flexsim simulation environment, we created Automatic Storage& Retrieval System simulation models. Based on the utilization rates of conveyors and stackers analyzed by Flexsim, this paper was focused on the key parts of the model to solve the bottleneck problem to maximize the efficiency of the system in the end.