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This paper aims to develop bilayer woven fabrics with different picking sequences with enhanced comfort without any change in the constituent materials.

Six bilayer woven fabrics were produced on Dobby loom with 3/1 twill weave using micro-polyester yarn. Three different picking sequences, i.e. single pick insertion (SPI), double pick insertion (DPI) and three pick insertion (3PI), were used in both face and back layers. The effect of picking sequence on air permeability (AP), volume porosity, thermal resistance and overall moisture management capability (OMMC) of the samples were analyzed.

The results showed that 3PI–3PI picking sequence gives the highest OMMC, AP and thermal resistance in bilayer woven fabrics and the least results exhibited by SPI–SPI picking sequence.

This research uses a bilayer woven system that develops channels and trapes the air causing higher thermal resistance; therefore, applicable for winter sports clothing rather than for summer wear. Developed bilayer woven fabrics can be used in winter sportswear to improve the comfort of the wearer and reduce fatigue during activity.

Authors have developed bilayer fabrics by changing the picking sequences, i.e. SPI, DPI and 3PI of weft yarns in both layers and compared their thermo-physiological comfort properties.

Two researchers suggest a new approach to the most fundamental warehousing operation of all.

This study is concerned with evaluating the performance of different storage policies and tour construction procedures for multi‐command picking using automated storage‐retrieval systems (AS/RS). The AS/RS machine travel time for each storage policy is derived as a function of the shape of the storage area, the number of picking points and the sequencing algorithm used. The combination of these variables yields various solutions to the problem, thus providing a useful guide in designing effective picking systems. The average travel time of the AS/RS in each configuration is calculated by computer simulation in a full factorial experimental design. A subset of the results derived from this study has been successfully implemented in a case study, involving the BMW AG Italy spare parts distribution warehouse.

The Industry 4.0 initiative – with its ultimate objective of revolutionizing the supply-chain – putted more emphasis on smart and autonomous systems, creating new opportunities to add flexibility and agility to automatic manufacturing systems. These systems are designed to free people from monotonous and repetitive tasks, enabling them to concentrate in knowledge-based jobs. One of these repetitive functions is the order-picking task which consists of collecting parts from storage (warehouse) and distributing them among the ordering stations. An order-picking system can also pick finished parts from working stations to take them to the warehouse. The purpose of this paper is to present a simplified model of a robotic order-picking system, i.e. a mobile manipulator composed by an automated guided vehicle (AGV), a collaborative robot (cobot) and a robotic hand.

Details about its implementation are also presented. The AGV is needed to safely navigate inside the factory infrastructure, namely, between the warehouse and the working stations located in the shop-floor or elsewhere. For that purpose, an ActiveONE AGV, from Active Space Automation, was selected. The collaborative robot manipulator is used to move parts from/into the mobile platform (feeding the working stations and removing parts for the warehouse). A cobot from Kassow Robots was selected (model KR 810), kindly supplied by partner companies Roboplan (Portugal) and Kassow Robotics (Denmark). An Arduino MKR1000 board was also used to interconnect the user interface, the AGV and the collaborative robot. The graphical user interface was developed in C# using the Microsoft Visual Studio 2019 IDE, taking advantage of this experience in this type of language and programming environment.

The resulting prototype was fully demonstrated in the partner company warehouse (Active Space Automation) and constitutes a possible order-picking solution, which is ready to be integrated into advanced solutions for the factories of the future.

A solution to fully automate the order-picking task at an industrial shop-floor was presented and fully demonstrated. The objective was to design a system that could be easy to use, to adapt to different applications and that could be a basic infrastructure for advanced order-picking systems. The system proved to work very well, executing all the features required for an order-picking system working in an Industry 4.0 scenario where humans and machines must act as co-workers. Although all the system design objectives were accomplished, there are still opportunities to improve and add features to the presented solution. In terms of improvements, a different robotic hand will be used in the final setup, depending on the type of objects that are being required to move. The amount of equipment that is located on-board of the AGV can be significantly reduced, freeing space and lowering the weight that the AGV carries. For example, the controlling computer can be substituted by a single-board-computer without any advantage. Also, the cobot should be equipped with a wrist camera to identify objects and landmark. This would allow the cobot to fully identify the position and orientation of the objects to pick and drop. The wrist camera should also use bin-picking software to fully identify the shape of the objects to pick and also their relative position (if they are randomly located in a box, for example). These features are easy to add to the developed mobile manipulator, as there are a few vision systems in the market (some that integrate with the selected cobot) that can be easily integrated in the solution. Finally, this paper reports a development effort that neglected, for practical reasons, all issues related with certification, safety, training, etc. A future follow-up paper, reporting a practical use-case implementation, will properly address those practical and operational issues.

A hybrid storage assignment (combination class-volume-based) framework considering quality proximity, customer and material categorization are key distinguished contents of this paper. In spite of using individual storage allocation approach, the hybrid allocation policy performs better under certain environment. The paper aims to discuss these issues.

Although it has been proved that every storage assignment policy has their advantages and limitations, one or more storage assignment policies with combination of zoning and layout design can be used together for further improvement. The authors have conducted this study at warehouse of a manufacturing firm that produce only single product with varieties of material and quality criteria. Picking optimization includes elimination of non-value-added activities like unwanted forklift and package movements, time and distance traveled for retrieval as well as storage. Other allied operations with respect to customer acceptance level and resource utilization are also considered.

The time and distance from manufacturing point to storage location are accountable as it also contributes to picking performance.

Quality-based cluster analysis is carried out to find out closeness among customers, which is used to propose algorithm with new layout design, zoning and storage allocation policy.

The effectiveness of product replenishment and responsiveness of customer service delivery impact largely on satisfaction and retention of customers in retail chain logistics distribution. The fast moving goods in the complex delivery network and limited vehicle resource often lead to long customer waiting time in stock replenishment. With lack of literature systematically reviewing factors affecting retail distribution in inter-store stock transfer services and improving the operations, the purpose of this paper is to analyse and enhance this service for the retail to reduce customer dissatisfaction by developing an integrated quality service improvement methodology and an optimisation tool to improve the product delivery services.

This paper reviews inter-store stock transfer operations and the process capability of an international retail chain, and proposes improvements by integrating Six Sigma, factor analysis, and optimisation modelling. User experience and expectations are evaluated through an empirical survey. A novel principle component factored inter-store stock transfer model is developed to improve replenishment operations. A total of 11 factors affecting inter-store stock transfer delivery time are analysed. An extended model with principal component factors incorporated is developed for the simulation.

The C_pk value of 0.51 shows significant difference between the experienced and expected waiting time. With the inter-store stock transfer optimisation model developed, the model assists traffic personnel on the vehicle route planning with multiple pick-up and drop-off locations. The system also ensures the best routing with a minimal travelling time planned, facilitating a reduction of the inter-store stock transfer time, thus improving the customer waiting time. Four significant factors affecting the delivery time are also identified from exploratory and confirmatory factor analysis. The results are analysed with an extended principal component factored inter-store stock transfer model.

The developed inter-store stock transfer models minimise stock transfer time, increase customer satisfaction, and reduce loss of sales. An integrated service quality improvement methodology has been developed and applied in reviewing significant factors affecting inter-store stock transfer operations.

This paper presents an analysis on inter-store stock transfer operations of an international retail and proposes enhancements on the operations by integrating Six Sigma, factor analysis, and optimisation modelling. A novel principal component factored inter-store stock transfer model is developed to improve the stock replenishment operations.

Wholesalers Wright & Green, well‐known in the voluntary group movement and part of the Linfood group, have become the first company to adopt Computer Automation's SyFA system. Applications will include sales order processing, financial accounting, stock and management accounting, and cash and carry price control.

Surface mount technology (SMT) is being increasingly used in printed circuit board (PCB) assembly. The reduced lead pitch of surface mount components coupled with their increased lead count and packing densities have made it imperative that automated placement methods be used. However, the SMT placement process is often a bottleneck in surface mount manufacturing. A reduction in placement time in SMT will enhance throughput and productivity. This paper describes the design and development of a prototype expert system based approach which identifies ‘near’ optimal placement sequences for surface mount PCBs in (almost) realtime. The software structure used integrates a knowledge based system with an optimisation module. PROLOG is the language used in this research. The system was rigorously validated and tested. Ideas for further research are also presented.

Storing and handling for the mail‐order market presents problems because of the large number of small items or cartons. Chris Askew, chief industrial engineer of the major UK mail‐order house Kay & Co., outlines his company's carton store which is designed to overcome handling problems. He describes its operation and overviews the computer system and management information produced by the system. Its success is judged by the fact that Kay's sister company GUSCO has adopted the same principle.

Vertical lift module (VLM) is a parts-to-picker system for order picking of small products, which are stored into two columns of trays served by a lifting crane. A dual-bay VLM order picking (dual-bay VLM-OP) system is a particular solution where the operator works in parallel with the crane, allowing higher throughput performance. The purpose of this paper is to define models for different operating configurations able to improve the total throughput of the dual-bay VLM-OP system.

Analytical models are developed to estimate the throughput of a dual-bay VLM-OP. A deep evaluation has been carried out, considering different storage assignment policies and the sequencing retrieval of trays.

A more accurate estimation of the throughput is demonstrated, compared to the application of previous models. Some use guidelines for practitioners and academics are derived from the analysis based on real data.

Differing from previous contributions, these models include the acceleration/deceleration of the crane and the probability of storage and retrieve of each single tray. This permits to apply these models to different storage assignment policies and to suggest when these policies can be profitably applied. They can also model the sequencing retrieval of trays.