Material Handling Devices Research Articles

A Novel Approach for Material Handling-Driven Facility Layout

Material handling is a widely used process in manufacturing and is generally considered a non-value-added process. The Dynamic Facility Layout Problem (DFLP) considered in this paper minimizes the total material handling and re-arrangement cost. In this study, an integrated DFLP model with unequal facility areas, assignment of material handling devices (MHD), and flexible bay structure (FBS) is considered, and it is aimed to propose fast solution approaches. Two different solution methods are proposed for the problem, which are the genetic algorithm and the simulated annealing algorithm, respectively. In both methods, a non-linear mathematical model solution was used to calculate the fitness values. Thus, the solutions in the feasible solution space are utilized. The proposed solution approaches were applied to solve four problems published in the literature. The computational experiments have validated the effectiveness of the algorithms and the quality of solutions produced.

ANALYSING THE EMERGING PRODUCTION TECHNOLOGIES IN CLOTHING INDUSTRY: PERCEPTION OF FASHION DESIGNERS WITHIN ADENTA MUNICIPALITY, GHANA.

This paper aims to investigate the emerging production technologies in clothing production in Ghana and the awareness and usage by fashion designers. The research was based on quantitative and studio-based approaches, which employed questionnaires and observation for data collection. The population comprises 120 fashion designers who have their workshops within Adenta. The results indicated that the emerging production technologies in the clothing industry were ranked, and Computer-aided design (CAD) represented first (1st), Automated inspection (AIN) ranked second (2nd) and Automated material handling devices (AMHD) ranked third (3rd). The study showed that 82.1 % of the respondents agreed that fashion designers' design activities involve the effective use of computers for drawing and designing products. Also, 86% agreed that fashion designers used automated inspection machines to perform inspections. However, 83.3% of the respondents disagreed that fashion designers use a reprogrammable, multifunctional manipulator designed for the automation of assembly lines for apparel making. The study concluded that to demonstrate creative and professional skills, fashion designers should be able to generate original designs from unique concepts and effectively manipulate most of the emerging production technologies in realising their concepts.

Pallet Distribution Affecting a Machine’s Utilization Level and Picking Time

Space and labor are the two internal resources within a warehouse or cross-dock center which seek attention. Meaningful efforts in optimizing these two resources can reduce the operational cost or time of the goods delivery. The timely allocation of resources to order picking not only reduces the makespan and operational time but can also evade delay. In decentralized settings, where all the information is not properly shared between the players of the supply chain, miscommunication results in delays in product delivery. In this study, efforts were made to determine the pallet quantity of different product types in an order quantify when there is a gap in information shared and, based on that, the allocation of material handling devices or pickers was conducted. Each handling device is bounded by a workload to eliminate the option of idle resources and ensure it is utilized properly. A mixed integer linear programming model was formulated for this study and was solved using Lingo. Numerical experiments were performed under varying resource numbers and pallet quantities to investigate the circumstances where the number of pallet types and allocation of machines have the highest benefit. The results confirm that a change in the pallet quantity of the products increases the total picking time. However, an increase in the number of handling devices minimizes the level of over-utilization of a particular machine.

Integration of material handling devices assignment and facility layout problems

Facility layout problems focus on the assignment of departments into the facility layout by considering the minimization of total costs. A well-designed facility result in efficient material flows in transportation. For this reason, the problem should be considered with the changes in demands that cause different material flows between departments. While the aim of the static facility layout problem is to obtain the optimal facility layout, the dynamic facility layout problem includes the multi-periods dealing with the changes in material flows between departments. Furthermore, the material handling devices may affect the facility layout decisions although it is omitted in general. In this study, three different facility layout problems concern static, dynamic and flexible bay structure and material handling device assignment problems are considered simultaneously. Three mixed integer programming models are proposed for the addressed problems with integrated decisions. The proposed models are compared with a two-stage approach composed of solving the classical facility layout problems first, then solving material handling devices assignment problems. The comparative results show that the integrated decision affects the facility layout and decreases the total costs. Eleven test instances are considered and the integrated model provides cost efficiency for these test instances.

A mixed-integer programming formulation of the double row layout problem based on a linear extension of a partial order

The double row layout problem (DRLP) occurs in automated manufacturing environments, where a material-handling device transports materials among machines arranged in a double-row layout, i.e. a layout in which the machines are located on either side of a straight line corridor. The DRLP is how to minimize the total cost of transporting materials between machines. The problem is NP-Hard and one great challenge nowadays is how to solve problem instances in reasonable computational times. In this paper, we give a new mixed-integer programming model of the DRLP, which is based on a linear extension of a partial order. In addition, we propose a reformulation of this model, which yields stronger results. The new models have the least number of 0–1 variables in comparison with previous models in the literature. Computational experiments demonstrate that the proposed models obtain optimal solutions faster than previously published ones.

Comparative study of autonomous production control methods using simulation

Manufacturing companies need to be effective in meeting customers’ delivery requirements. Due to customers’ expectations of shrinking delivery times, manufacturing lead times need to be short. This can be achieved through efficient Production Activity Control (PAC) methods. Currently PAC methods rely mostly on centralized decision-making and, seeming not to be adequate to deal with the increasing complexity and dynamics of manufacturing. Autonomous Production Control (APC) methods are a promising alternative to current methods, due to their rapid and flexible reaction to disturbances of the production systems’ operation. APC methods transfer the power of decision-making from a central unit to distributed logistic objects, such as machines, jobs and material handling devices. In this study, three APC methods, namely Pheromones (PHE), QLE (Queue Length Estimator) and a refined version of QLE (RQLE), are compared and analysed via simulation. The study was accomplished for two shop configurations, namely a flexible flow shop and a general flexible flow shop. Simulation results show a superior performance of RQLE in both configurations. Results also show that a new dispatching rule here proposed, the SPT-RTT rule, performs better than others with which it was compared. The study may have important implications for industrial practice and future research in PAC.

Identification and classification of materials using machine vision and machine learning in the context of industry 4.0

Manufacturing has experienced tremendous changes from industry 1.0 to industry 4.0 with the advancement of technology in fast-developing areas such as computing, image processing, automation, machine vision, machine learning along with big data and Internet of things. Machine tools in industry 4.0 shall have the ability to identify materials which they handle so that they can make and implement certain decisions on their own as needed. This paper aims to present a generalized methodology for automated material identification using machine vision and machine learning technologies to contribute to the cognitive abilities of machine tools as wells as material handling devices such as robots deployed in industry 4.0. A dataset of the surfaces of four materials (Aluminium, Copper, Medium density fibre board, and Mild steel) that need to be identified and classified is prepared and processed to extract red, green and blue color components of RGB color model. These color components are used as features while training the machine learning algorithm. Support vector machine is used as a classifier and other classification algorithms such as Decision trees, Random forests, Logistic regression, and k-Nearest Neighbor are also applied to the prepared data set. The capability of the proposed methodology to identify the different group of materials is verified with the images available in an open source database. The methodology presented has been validated by conducting four experiments for checking the classification accuracies of the classifier. Its robustness has also been checked for various camera orientations, illumination levels, and focal length of the lens. The results presented show that the proposed scheme can be implemented in an existing manufacturing setup without major modifications.

Overhead Travelling Crane Construction Deflection Measurements with Telematic Approach

Abstract Transport has always been a fundamental impulse for the development of civilization. Issues related to the regularity of operation of technical systems, in the last decade have become important issues being considered from both the point of view, as well as economics. Today the major threat in the operational reliability constitutes intensification of the machine and equipment use leading to excessive degradation. In automated manufacturing processes where the material handling operations are realized by the cranes, the safety as both devices and operating people constitute important factor. The main purpose of the article was focused on the set of issues including the material handling devices (MHD) reliability shaping problem especially presents work in progress towards development the MHD condition assessment system with using telematic approach. In the article author, special care was enclosed to MHD devices with strength human factor interaction and relatively large construction, so the overhead travelling crane was chose. The object of the statement constitutes an attempt of collecting the knowledge concerning a possibility of use modern measurement systems to monitoring crane bridge deflection. All tests and considerations were conducted on the double girder overhead travelling crane with hosting capability 1000 kg and bridge span 8000 mm.

Design, Modelling and Manufacturing of 16 Cylinder Hydraulic Fixture with Automated Clamping System

The function of a jig and/or fixture (fixturing system) is to hold a workpiece firmly in position during a manufacturing process. It is seeming that almost all the literature of fixture is focused on principles and theoretical aspects of fixture design. This raises a question of the practical value of fixture research. There is a clear demand for designing and manufacturing fixture for real industrial component and more research in computerized fixture design in such fields. The present research work satisfies this demand by deploying the fixture design task into an overall manufacturing process to obtain best fixture design solution for real industrial component. The component is rear flange of gear case widely used in automobile industry, made up of cast iron. The major operations to be performed are drilling and milling. The research includes design and manufacturing of a fixture with automated clamping system, which provides location and clamping arrangement for machining 4 components in one cycle on VMC 640 of pallet size 800 mm x 500 mm. Machine tools, material handling devices, transport and other mobile equipment, aviation systems, etc. do use hydraulic systems, butapplication of hydraulic principles in fixture is of uncovered area till now. This paper includes designing and manufacturing 16-cylinder hydraulic fixture with automated clamping system for machining rear flange on VMC. The important details of the part and fixture are included in each section along with 2D drawing and 3D view of finished component and fixture assembly using Creo 2.0.Fixture is not only designed but manufactured also, it sets the classical example of design for manufacturing.

The Printed-Circuit-Board Electroplating Parallel-Tank Scheduling With Hoist and Group Constraints Using a Hybrid Guided Tabu Search Algorithm

Current research investigates a parallel-tank scheduling problem with hoist and group constraints in printed-circuit-board (PCB) electroplating environment, where the hoist is used as a material handling device and PCBs need to be grouped for further processing. The purpose of the current research is to minimize the makespan and total weighted tardiness of PCB products. The weighted ideal point method is used to combine these two objectives into a single optimization objective. Moreover, a mixed integer programming model is developed to formulate the problem. Since the problem is proved to be NP-hard, a hybrid guided tabu search (HGTS) algorithm is proposed to optimize the objectives. A heuristic method based on small combination sequences called SCS is applied to search the better initial solution. Moreover, a problem-oriented guided neighborhood move strategy is adopted to improve the search efficiency in the proposed HGTS algorithm. The experiments are conducted on different size of problem instances. The performance of the proposed HGTS algorithm is investigated and compared with other existing algorithms. The detailed results indicate that the proposed HGTS algorithm performs better both in objective value and convergence speed. Finally, a real-world case is solved by the proposed HGTS, which validates that the proposed algorithm is effective and useful in solving the practical electroplating scheduling problem.

A Water-Flow Like Algorithm for Solving U-Shaped Assembly Line Balancing Problems

The problem of assigning assembly tasks to the stations arranged along a material handling device is known as assembly line balancing. This paper aims to address the U-shaped assembly line balancing problem (UALBP) which arises when a U-shaped assembly line has to be configured. It is widely known that this problem is NP-hard. Accordingly, different meta-heuristics based on a single solution (such as Simulated Annealing) or a population of solutions (such as Genetic Algorithms) have been proposed in the literature. Meanwhile, it has been argued that either of these meta-heuristics with a fixed number of solutions cannot maintain efficient search progress and thus can lead to premature convergence. Thus, this study aims at adopting a novel meta-heuristic algorithm with dynamic population sizes, namely Water Flow-like Algorithm (WFA), inspired by the behaviour of water flows in nature, to address the UALBP. The line efficiency and variation of workload are considered as the primary and the secondary objective, to be optimized, respectively. To verify the efficiency and robustness of the proposed WFA, a real case study taken from an automobile manufacturer as well as a set of standard problems are solved and the results compared with the existing approaches in the literature. The computational results demonstrate the superiority of the WFA, particularly in addressing medium to large-sized problems.

Integrated scheduling of part, tool and automated guided vehicles in a flexible manufacturing system using modified genetic algorithm

Scheduling of part and tools without considering material handling devices may result into non-implementable results as the material handling system constraints affect the overall scheduling. In this paper, an attempt has been made for the simultaneous scheduling of part, tool and two automated guided vehicles (AGVs) in a flexible manufacturing system which has identical machines with no on-board tool magazine. All the tools are stored in a common tool magazine and are shared among different machines through a material handling system. Each tool type is single in number. The problem has two interrelated problems; one as loading and scheduling of part and tool and other as scheduling of AGVs. Two heuristics namely priority dispatching rules (PDRs) and modified genetic algorithm (MGA) with three parent crossover are used to find the optimal solution to the integrated scheduling problem. Both PDRs and MGA use an algorithm based on the concept of Giffler and Thompson procedure and a heuristic approach to generate the active feasible schedule. The performance of the two proposed algorithm is compared for the results of makespan. It was found that the MGA gives better results.

Integrated scheduling of part, tool and automated guided vehicles in a flexible manufacturing system using modified genetic algorithm

Scheduling of part and tools without considering material handling devices may result into non-implementable results as the material handling system constraints affect the overall scheduling. In this paper, an attempt has been made for the simultaneous scheduling of part, tool and two automated guided vehicles (AGVs) in a flexible manufacturing system which has identical machines with no on-board tool magazine. All the tools are stored in a common tool magazine and are shared among different machines through a material handling system. Each tool type is single in number. The problem has two interrelated problems; one as loading and scheduling of part and tool and other as scheduling of AGVs. Two heuristics namely priority dispatching rules (PDRs) and modified genetic algorithm (MGA) with three parent crossover are used to find the optimal solution to the integrated scheduling problem. Both PDRs and MGA use an algorithm based on the concept of Giffler and Thompson procedure and a heuristic approach to generate the active feasible schedule. The performance of the two proposed algorithm is compared for the results of makespan. It was found that the MGA gives better results.

A Novel Gripper design for Diaphragm spring plate Pick and Place Cobot

Robot integrated manufacturing has turned out to be the future of manufacturing automation technology. Worker assisting robots perform simultaneously operation including machining, assembly, inspection, material handling etc. and in some case multiple operations in the same system at a faster and precise rate. Collaborative robots are human and computer controlled hybrid material handling device which facilitates the concept of shared workspace. To exploit its function, gripper mechanisms are inevitable. This project focuses on the design of cobotic grippers for pick and place application. Of the different concepts compared a suitable design is chosen. The gripper moves according to the signals received from the cobot, sensors and PLC control system.

Evaluation of batching and layout on the performance of flexible manufacturing system

Flexible manufacturing system (FMS) is one of the solutions that enables any manufacturing system to withstand changing requirements of the market. An FMS consists of different automated workstations, material handling devices, and storage systems, all of which work under computer control. In the present work, analysis and modeling of a real problem has been considered for performance improvement. Modeling is done for analyzing the performance of an existing model, to propose a new layout for the system. Effect of factors like part mix, layout type, and batching condition, on the system performance in terms of productivity, system utilization rate, and cycle time is analyzed. The work includes simulation study along with Taguchi’s experimental design framework for studying how different factors with varying levels affect system performance. ProModel software is used for simulating existing and proposed models of the manufacturing firm. Further, analysis of variance (ANOVA) is employed for finding the most important factor that affects system performance. Proposed methodology helps in determining best factor-level combination for each performance parameter. The results show that the system performs well with the implementation of loop layout having many numbers of batches. Towards the end, the scope of further is highlighted.

Scheduling of mobile robots for transportation and manufacturing tasks

Current manufacturing systems have a tendency to become more and more flexible to adapt to the needs of product diversification. Such a system, e.g. flexible manufacturing system, consists of a number of automatic machines, material handling devices such as automated guided vehicles (AGVs) or mobile robots, and a central control computer. Mobile robots, as well as AGVs, can move around in their working space to transport components among machines. The main novelty of this work is that mobile robots can also execute various value-added tasks without human intervention thanks to their manipulation arms which is not possible for AGVs. This new characteristic certainly makes the problem more complex and computationally expensive. To utilize these manufacturing systems in an efficient manner, it is necessary to schedule transportation of product components by mobile robots and to schedule processing of products on machines possibly by mobile robots. Consequently, the key innovation of this work lies in consideration of three interrelated sub-problems which must be solved. They include computing the sequence of operations on machines, the robot assignment for transportation, and the robot assignment for processing. To achieve this goal, a computationally efficient hybrid heuristic method combining genetic algorithm and tabu search is developed to solve the problem considering makespan minimization. A mixed-integer programming (MIP) model is formulated. Another combined method using results of the hybrid heuristic is proposed to speed up the solving of MIP model. The quality of hybrid heuristic’s solutions is compared and evaluated by using those of the MIP model as reference points.

Fault Tree Analysis for Reliability Evaluation of an Advanced Complex Manufacturing System

In this paper, minimal paths and cuts technique is developed to handle fault tree analysis (FTA) on the critical components of industrial robots. This analysis is integrated with the reliability block diagram (RBD) approach in order to investigate the robot system reliability. The model is implemented in a complex advanced manufacturing system having autonomous guided vehicles (AGVs) as material handling devices. FTA grants cause and effects and hierarchical properties to the model. On the other hand, RBD simplifies the complex system of the AGVs for reliability evaluation. The results show that due to the filtering of the paths in a manufacturing system for AGVs, the reliability is highly dependent on the mostly occupied paths by AGVs. The failure probability for the AGV is considered to follow the exponential probability distribution and thus the whole system reliability using minimal paths and cuts method is obtained 0.8741.

Towards Developing Sustainable Reconfigurable Manufacturing Systems

This paper aims to examine the sustainable manufacturing performance of Reconfigurable Manufacturing Systems (RMSs) using existing sustainable manufacturing metrics. RMS has six key characteristics including modularity, integrability, customization, scalability, convertibility, and diagnosability. In this paper, ‘convertibility’ is quantified by considering configuration convertibility, machine convertibility, and material handling device convertibility from the RMS perspective. In addition, the performance of RMSs with different convertibility levels is also evaluated by using sustainable manufacturing metrics. A numerical example is used to demonstrate the computational approach. Results of the analysis are used to show how sustainable manufacturing performance of RMS changes as system convertibility varies. The findings show that RMS sustainable manufacturing performance can be improved by selecting a suitable level of convertibility.

Preliminary design of a production automation framework for a pyroprocessing facility

Abstract Pyroprocessing technology has been regarded as a promising solution for recycling spent fuel in nuclear power plants. The Korea Atomic Energy Research Institute has been studying the current status of equipment and facilities for pyroprocessing and found that existing facilities are manually operated; therefore, their applications have been limited to laboratory scale because of low productivity and safety concerns. To extend the pyroprocessing technology to a commercial scale, the facility, including all the processing equipment and the material-handling devices, should be enhanced in view of automation. In an automated pyroprocessing facility, a supervised control system is needed to handle and manage material flow and associated operations. This article provides a preliminary design of the supervising system for pyroprocessing. In particular, a manufacturing execution system intended for an automated pyroprocessing facility, named Pyroprocessing Execution System, is proposed, by which the overall production process is automated via systematic collaboration with a planning system and a control system. Moreover, a simulation-based prototype system is presented to illustrate the operability of the proposed Pyroprocessing Execution System, and a simulation study to demonstrate the interoperability of the material-handling equipment with processing equipment is also provided.

Multi-agent-based hierarchical collaborative scheduling in re-entrant manufacturing systems

Production scheduling problems in re-entrant manufacturing systems are complex due to their features of large-scale complexity, unbalanced workload and dynamic uncertainty. The aim of this paper is thus to develop an effective way of formulating production schedules for designing RMSs. First, a multi-agent-based hierarchical collaborative system consisting of a system layer, a machine layer, and a material handling device layer is developed to improve the efficiency of RMSs. The objective of the system layer is to maximise the total processing profit, and the objective of the machine layer is to determine the winning bid. Second, a contract net protocol scheduling algorithm is applied to solve capacity planning problems for key machine groups in the system layer. Third, a generalised partial global planning-contract net collaborative mechanism is adopted to allocate tasks to machines within each machine group in the machine layer. Finally, the performance of the proposed approach is validated through a case study, and the results demonstrate that the proposed approach outperforms the first-come first-serve rule in combination with the minimised batch size rule in terms of daily movement and machine utilisation.