Multiple Workstations Research Articles

An intelligent climate monitoring system for hygrothermal virtual measurement in closed buildings using Internet-of-things and artificial hydrocarbon networks

Studies analyzing indoor thermal environments comprising temperature and humidity may be insufficient when obtaining data from sensors, which may be susceptible to inaccurate or failed information from internal and external factors. Therefore, this study proposes an intelligent climate monitoring using a supervised learning method for virtual hygrothermal measurement in enclosed buildings used to predict temperature and relative humidity when a sensor failure is detected. The methodology comprises the data collection from a wireless sensor network, the building of the learning model for predicting the dynamics of environmental variables, and the implementation of a sensor failure detection model. We use an artificial hydrocarbon network as the learning model for their simplicity and effectiveness under uncertain and noisy data. The experiments use data acquired in two settings: (1) a laboratory office and (2) a museum storage room. The first scenario has multiple workstations, and the staff turns on or off the air conditioning depending on the feeling of comfort, generating an uncontrolled environment for the variables of interest. The second scenario has controlled temperature and humidity to ensure the conservation conditions of the museum pieces. Both scenarios used 12 sensors that acquired data for one month, providing an average of 58,300 values for each variable. Results of the proposed methodology provide 95% of accuracy in terms of sensor failure detection and identification, and less than 0.22% of tolerance variability in temperature and humidity after sensor accommodation in both scenarios.

Allocating Robots/Cobots to Production Systems for Productivity and Ergonomics Optimization

Collaboration between humans and robots has great promise in manufacturing systems. The utilization of cobots in a manufacturing system can improve both productivity and ergonomics. In this paper, we study the problem of how to allocate limited cobot/robots to manufacturing systems with multiple workstations so that an integrated performance measure, considering both productivity and ergonomics is optimized. Previous work on cobot/robot allocation in manufacturing systems focus on the decomposition of tasks for a single workstation into multiple work elements, and then split them between human and robots, rather than studying multi-machine systems. To bridge this gap, we consider the allocation of cobots/robots to a multi-stage manufacturing system. Specifically, we establish an integrated performance measure and formulate cobot/robot allocation into a constraint integer programming problem. With this formulation, we obtain the optimal allocation of one available cobot/robot in simulated production systems, based on the integrated performance measure of productivity and ergonomics. Furthermore, the allocation problems of production systems with multiple cobots/robots is considered and solved with a scalable algorithm. <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">Note to Practitioners</i> —Collaborative robots and independent robots are increasingly applied to manufacturing production systems. However, how to optimally allocate both types of robots considering both productivity and ergonomics influence has not been well studied. In this article, we established a practical optimization method to allocate cobots/robots to different workstations and split the work between cobot and human in one workstation when there are multiple workstations and a limited number of available cobots/robots in the manufacturing systems. Based on various real-world scenarios, we inferred useful insights for the robot/cobot allocation problem. To deal with the computational load when the number of workstations is large, a scalable optimization algorithm is also adopted. The case study results demonstrated the effectiveness of the proposed approach.

Picking scheduling for single picker to multi-workstations of the part-to-picker order fulfilment system

To reduce human resource costs, the part-to-picker order fulfilment systems may have a single picker in charge of multiple workstations. And the picking speed of the picker becomes faster as the picking number increases due to the learning effect in the picking operation. In this paper, the scheduling problem to optimizing picking sequence of the picker is presented to minimize the maximum picking time, where one picker is responsible for multiple workstations. The learning effect and travel time between workstations are taken into account to improve scheduling accuracy. Two mixed integer programming (MIP) models are proposed to solve the problem, namely the rank-based model and disjunctive model. The performance of the two Mixed Integer Programming (MIP) models has been evaluated, and it has been found that they are only capable of solving small-scale problems. The rank-based model is limited to solving problems with up to 9 groups, whereas the disjunctive model can handle up to 20 groups. Therefore, the disjunctive model outperforms the rank-based model. Moreover, this paper proposes Interval Insertion NEH (IINEH) and iterative greedy (IG) algorithm to solve the large-scale problem. Numerical experiments demonstrate the effectiveness of the two methods to solve the problem, where IINEH operates faster while IG gives better results. Therefore, when faced with a large-scale problem, IINEH is recommended if a quick solution is needed. If better optimization results are needed, the decision maker can choose IG.

Virtual machine placement in energy aware load balancer using fog classifier

Cloud datacenter carries huge volume of data and tasks which is allocating resources to multiple workstations. Most of the cloud services are operating service level agreement (SLA) placements. During execution datacenter emits carbon and makes the energy. So operation cost always consideration fact. We need to address this challenge by using energy aware load balancer. This load balancer can be fixed in Virtual Machines (VM) and Classifier is required for selecting VMs. Employing the VMs is very important factor so fog enabled services is required for distributed geo physical load balancer with energy efficiency. In this paper we propose offloading VM services and Fog classifier for load balancing the cloud services. Placing the VM from one host to another we use Host Load Balancer with Energy Aware placement algorithm. In this case dynamical cloud environment can be tested and compare the host results. This is empirical approach for place the VMs without compromising the users. The simulations are done by using CloudSim and TensorFlow is used of generating deep belief network model for preparing VM placement. Our proposed method achieves 96% energy efficiency with minimum migration cost. The results are compared with existing placement methods based on active host availability.

Design and Implementation of Omnidirectional Mobile Robot for Materials Handling among Multiple Workstations in Manufacturing Factories

This paper introduces the mechanical design and control system of a mobile robot for logistics transportation in manufacturing workshops. The robot is divided into a moving part and a grasping part. The moving part adopts the mecanum wheel four-wheel-drive chassis, which has omnidirectional moving ability. The mechanical system is based on four mechanical wheels, and a modular suspension mechanism is designed. The grasping part is composed of a depth camera, a cooperative manipulator, and an electric claw. Finally, the two are coordinated and controlled by computer. The controller hardware of the mobile platform is designed, and the functional modules of the mobile platform are designed based on the RT thread embedded system. For the navigation part of the mobile robot, a fuzzy PID deviation correction algorithm is designed and simulated. Using the Hough circular transform algorithm, the visual grasping of the manipulator is realized. Finally, the control mode of the computer-controlled manipulator and the manipulator-controlling mobile platform is adopted to realize the feeding function of the mobile robot, and the experimental verification is carried out.

Designing Simulation to Improve Production Efficiency of Batik Industry

Background The study deals with evaluating the production system for manufacturing batik, then developing a scenario for improving the system. Purpose The study aims to point out the possibilities of computerized simulations in designing, testing, and exploring scenario models of real production plants of Small-Medium enterprises (SMEs). Method The research is carried out as a case study, using a simulation approach to achieve the objectives. This study uses three data collection techniques: direct observation, qualitative interviews, and time study. The simulated model of the system is the basis for building improvement strategies. Results The simulation model yields more than 70% of the overall process time mainly consisting of idle time and waiting for the operator. It leads to an inefficient production system. Significant differences in processing time and assigning operators to workstations that are unbalanced cause inefficiency. Although most of the time was not efficient, the average utilization of the operator was 63.96%. The system has a good operator’s utility level because the average total utility value is higher than idle time. The operators are also responsible for other tasks that were included in the simulation. Discussion The study proves that simulation is a very promising approach that allows industrial owners to mimic the production process and resource assignments within the model. The production efficiency with existing resources can be enhanced with the balancing procedure between the workstations and the operators. The suggested system runs on the concept of assigning operators with lower utility to processes with high WIP queues. The operator can interact with multiple workstations. The proposed model reduces the total time required to produce the batik. Contribution The simulation helps the analyzed organization to evaluate the efficiency of the manufacturing process. Changing the parameters in the model can generate new utilization and efficiency for the system.

Design Method for Automatic Assembly Production Line of Electric Valves in Space Propulsion Systems

This article proposes a design method for a valve automatic assembly production line in response to the automation assembly requirements of electric valve products in space propulsion systems and the engineering problems of inaccurate loading force control and low valve measurement accuracy in existing process methods. This method can achieve five assembly processes during the assembly process of electric valves, including pre-tightening force control, valve-core stroke measurement, performance testing, and shell structure welding. The article introduces the design of platform components such as process execution, positioning, and transportation, as well as the design and operation process of workstations. By combining the design of a three-axis motion mechanism, a small turntable, and a robotic arm, the product can achieve professional, positioning, full process automation, and equipment miniaturization design across multiple workstations. Through the design of precise control of loading force and non-contact optical measurement method of moving structure, compared with the original method, the parameters affecting product performance are precisely controlled and the precision is improved. And the multivariable decoupling of valve product performance is realized by this method. Through application verification, this automatic assembly production line can significantly improve the assembly efficiency of electric valve products and solve difficult problems in product engineering.

Drone Optimization in Factory: Exploring the Minimal Level Vehicle Routing Problem for Efficient Material Distribution

The efficient movement of raw materials within organizations is fundamental to maintaining the seamless progression of production processes. However, these logistical operations can inadvertently compromise overall company efficiency, primarily due to the substantial time invested in transporting materials. This paper introduces an innovative mathematical model specifically designed to optimize the transport of raw materials via drones across multiple workstations. This model employs a novel modification of the traditional multi-level Vehicle Routing Problem by incorporating an additional index and accounting for the drone’s energy consumption. We employ a widely-recognized solver for practical resolution and compare it with a heuristic algorithm. The resultant strategies offer promising prospects for the organization studied, introducing robust solutions for elevating the efficiency of raw material transportation.

Investigating the Ergonomic Work Posture on Traditional Fishing Boats Manufacturing in Lhokseumawe City, Aceh Province, Indonesia

The Sailing ships in Aceh are usually conventional; this shipbuilder usually requires 3 people. Sailing ships in Aceh are usually made conventionally. Shipbuilders need 3 workers. Construction time for ships weighing 1 to 3 gross tons (GT) takes 1 - 2 months. Strategies and improvements in shipbuilding methods have been well-studied in the shipbuilding literature. The location and process of making the ship are in the Banda Sakti sub-district, Lhokseumawe City. It has multiple workstations, such as measuring and cutting stations and assembly stations. Operators must work 8 hours daily in various postures, including standing, bending, and lifting heavy objects. On the basis of the preamble of the Nordic Body Map (NBM), intense exercise damages the musculoskeletal system by comparing the Rapid Upper Limb Assessment and Rapid Entire Body Assessment for workers' assessment of their working posture. In the process of making fishing boats. Results of REBA Labor Calculation: Worker 1 gets a score of 9, Worker 2 gets a score of 11, and Worker 3 gets a score of 5. In RULA, Workers 1 and 2 get the same score of 6, and Worker 3 gets the same score of one score out of 4. REBA received a final score of 2 at low-risk level 1, and REBA 2 workers received a final score of 2 at level 1, low-risk, and performance level 1. Working conditions at lifting stations must be improved to prevent musculoskeletal system diseases in the timber lifting station employees.

An automated guided vehicle conflict-free scheduling approach considering assignment rules in a robotic mobile fulfillment system

Automated guided vehicle (AGV), as a material handling equipment, has been widely used in various applications, especially in the automated warehouse of manufacturing. The working efficiency of the warehouse is greatly influenced by the organization of the order picking process. As the picking tasks of AGVs increase in a certain period, conflicts and deadlocks of simultaneously working AGVs occur more frequently, which are also defecting factors of efficiency. In this paper, a multi-AGV scheduling approach considering assignment rules (MASA) is proposed, and a stage conflict avoidance method is designed to generate a conflict-free working route for AGVs in an automated warehouse with multiple workstations. Different from the random assignment rule of workstations in previous studies, the crowding-based assignment rule (CAR) and opening-time-based assignment rule (OTAR) are proposed to adjust the AGV working route and alleviate the congestion of AGV at the workstations. The scheduling model of AGVs is constructed to minimize the total completion time based on a space–time network, and a cooperative optimization algorithm is designed to solve the AGVs conflict-free scheduling problem. Numerical experiments verify the effectiveness and stability of the proposed algorithm. With the same working loads, CAR and OTAR result in a 5.55% and 9.56% decrease in the total completion time than the traditional random assignment rule, and the completion time is reduced by 8.01% and 12.13% in class-based tasks, respectively. MASA has great potential to improve the system efficiency of the warehouse when there are massive picking tasks and workstations.

Patient Specific Quality Assurance Automation with Scripting on HID Devices

<h3>Purpose/Objective(s)</h3> Many quality assurance procedures in radiotherapy are tedious and time-consuming but can be automated to improve the efficient and minimum human-errors. In this study we focused on the patient specific quality assurance (PSQA) procedure. The purpose was to develop a robust and quick software interface for Human Interactive Device (HID) operations and significantly accelerate the workflow. <h3>Materials/Methods</h3> The clinical PSQA system of our clinics consists of s treatment planning system (TPS), an oncology information system (OIS) and a measurement and analysis software. The complete PSQA process includes three main parts: (1) QA verification plan creation, (2) treatment plan loading to treatment machine and (3) measurement, data analysis and report. A homemade software tool, AUTOFLOW was developed as a general interface and installed on multiple workstations to automate the operations of local HID devices. The workflow of HID operations in these components was modularized for maximum efficiency and reliability. The required patient information for each computer was stored in a QA task file created from patient database and synchronized by the AUTOFLOW interface in individual workstations. All human operations on HID devices and communication between multiple computers were automated by the AUTOFLOW interface sequentially or parallelly during the entire PSQA process. <h3>Results</h3> We tested the developed automation workflow on 20 clinical QA plans in our current clinical environments. Overall, around 175 (±12) human HID operations on various workstations were removed from the PSQA procedure. On average, 8(±0.8) minutes was needed to complete a PSQA case with the AUTOFLOW software tool, compared to 13(±3.1) minutes for complete manual operations. These results represent a 38% saving in time. No errors were found for all operations performed with this interface. <h3>Conclusion</h3> The AUTOFLOW software interface was successfully developed and used to perform PSQA in our current clinical environment. This interface has substantially reduced the time, and eliminated user stress and input errors for our PSQA procedure. It can potentially work with other TPS, QA, R&V systems of our department to improve the efficiency and reduce human errors for other QA procedures. For future works we plan to improve the system flexibility/stability and implement this application to other QA procedures

Implementing the Concept of Alarm Flexibility During Production

An interruption at a workstation is a major cause of production downtime, which has negative effects on performance, cost, consumer-centric value, and efficiency. Blockage and starvation brought on by broken workstations have a domino effect on the entire production line. To allocate resources effectively and minimize downtime, it is crucial to thoroughly analyze each disruption's effects. Quantitative analysis of disruption at a single workstation and its effects on neighbouring workstations are performed in the work presented. Faulty workstations have an additional threshold value added to the Alarm Trip Point (ATP), depending on their current state. This one significantly improves upon downtime mitigation and batch rejection reduction compared to previous approaches. A more general model based on multiple workstations has been developed by expanding the analysis for a single workstation. The proposed work is demonstrated in an experimental case study, an Asphalt-Processing Plant. It is applied in addition to developing a theoretical model to reduce downtime, multiple starts and stops, and numerous rejections. The proposed method reduces start-stop events by 60%, reducing rejections and downtime while increasing consumer-centric value and efficiency.

Investigating two variants of the sequence-dependent robotic assembly line balancing problem by means of a split-based approach

The Robotic Assembly Line Balancing Problem (RALBP) is a joint optimisation problem that is concerned with assigning both assembly operations and robots to workstations that are placed within a straight line. RALBP-2 is the particular problem where the cycle time, which is the maximum time spent on a workstation by the product being assembled, is minimised while the number of workstations is fixed. Sequence-dependent setup times are considered which raises the problem of sequencing the operations assigned to each workstation. Both the durations of the operations and the setup times depend on the robot. Two different variants are identified from literature. The first variant assumes that, given a set of types of robots, each type of robot can be assigned to multiple workstations without any limitation. Given a set of robots, the second variant forces each robot to be assigned to at most one workstation. Both assumptions are studied in this paper. The particular case of a given giant sequence of operations is solved thanks to a polynomial optimal algorithm. The latter algorithm, called split, is then embedded in a metaheuristic framework that explores the space of giant sequences. Benchmark data sets from literature are considered in the experimental section. A comparative study with other methods from literature shows the competitiveness of the suggested approach.

A simulation-based statistical method for planning modular construction manufacturing

Modular construction is a promising alternative to conventional construction; offering improved productivity, quality, and safety. To realize these benefits, sequencing the module fabrication process in a manner that ensures efficient allocation of labor resources is essential. However, the varying sizes and design specifications of modules lead to high variation in process times at workstations, ineffective utilization of resources, and imbalanced production lines. To address these challenges, this paper proposes a simulation-based statistical method to plan the sequencing of module fabrication and the allocation of workers at workstations for such that productivity and control are improved. The method consists of four processes: (i) data collection to obtain historical and near real-time data; (ii) identification of significant impact factors affecting process times at workstations along the production line; (iii) development of a predictive model for forecasting process times at workstations using statistical analysis and probability distribution function; and (iv) planning the sequencing of module fabrication in a manner that ensures efficient labor allocation (i.e., crew size). The developed method is validated using data captured from a light gauge steel wall panel production line operated by a modular fabricator in Edmonton, Canada. The industrial partner produces both interior and exterior light gauge steel wall panels on a production line consisting of multiple workstations. First, five significant impact factors for each workstation among the design factors that highly influence the process times were identified in order to develop cycle time formula as a predictive model. The simulation model developed and implemented in conjunction with cycle time formula (CTF) in this case study was deemed to be a reliable predictive model (i.e. 89.39% accuracy), which can be used to improve productivity. The method is shown to be capable of assisting in decision-making by enabling production managers to better understand the effects of proposed changes to the production line prior to implementation. In this way, production managers can plan effectively and thereby reducing non-productive idle time.

Messtechnisch unterstützte Quantifizierung der Repetitionsbelastung des Hand-Arm-Systems bei manuellen Arbeitsprozessen an modernen Montagearbeitsplätzen und deren Bewertung

Measurement-based evaluation of the repetitive strain on the hand-arm system during manual work processes at modern assembly workplaces Objective: On both modern assembly lines and U-shaped lines, the workplaces comprise multiple workstations or work processes with differing requirements. This presents difficulties for recognition and assessment of the repetitive nature of the activity as a whole. This paper presents the measurement of repetitive strains on the upper extremities on real-case U-shaped assembly line systems. Methods: In a field study, a total of 24 workers in six plants in the metalworking and electrical engineering sectors were analysed at 18 different U-shaped assembly line workplaces. Movements of the hand-arm system and muscular activity of the hand flexor muscles (M. carpi ulnaris) and the trapezius muscles were recorded at each workplace over a period of between 1 and 2 hours by means of the CUELA measurement system and surface electromyography (EMG). Results: The medians of the angular velocities of the wrist varied between the different workplaces from a low of 2.4 °/s to a high of 20.5 °/s. Correspondingly, the average movement frequencies of the wrist lay between 0.23 and 0.43 Hz. Conversely, the micropause components (angular velocity &lt; 1 °/s for Δt &gt; 0.5 s) reached values between 13.5 % and 1.6 % of the working time. Without any evident relation to the kinematics, the surface EMG of the forearm flexors exhibited on average a dynamic (P90) load of around 20 % of the individual maximal voluntary EMG activity (MVE). At half of the workplaces however, the micro pauses (time component EMGRMS &lt; 0.5 % MVE) totalled only 10 % or less of the recorded working time. Conclusions: Repetitive strains on the hand-arm system were also quantified in the field at workplaces differing in their degree of automation and with alternating workstations. Although the dynamic forces that must be applied at modern assembly lines are generally quite moderate, the associated repetitive strains are often high. This must be taken into particular consideration when planning job rotation on assembly lines. Keywords: assembly line – manual work processes – U-shaped assembly line – repetitive strain – workload analysis based on measured data

Order picking optimization with rack-moving mobile robots and multiple workstations

In this paper, we study an automated warehousing system, where racks are moved by robots to multiple workstations so that pickers at each workstation can retrieve the products from the racks to fill up the orders. In this context, the order and rack sequences should be considered simultaneously and the workload balance and rack conflicts among multiple workstations should also be taken into considerations. However, these factors have not been addressed in the current literature. To fill this gap, we formulate a comprehensive multi-workstation order and rack sequencing problem as a mixed integer programming model that accounts for workload balancing and rack conflicts. To solve the model, we propose an adaptive large neighborhood search method, which builds on a newly developed data-driven heuristic that exploits the structure of the problem and simulated annealing. We show that our proposed approach performs well on both small-scale problem instances with synthetic data and a large-scale real-world dataset supplied by a large e-commerce company. In the latter case, it can save up to 62% in rack movements compared to the company’s current practice.

Non-Traditional Layout Design for Robotic Mobile Fulfillment System with Multiple Workstations

This paper studies the layout design of a robotic mobile fulfillment system with multiple workstations. This is a parts-to-picker storage system where robots hoist pods and bring them directly to the workstations for stationary pickers to retrieve required items. As few research efforts have focused on determining the optimal locations of workstations in such systems, we develop an integer programming model to determine the location of workstations to minimize the total traveling distance of robots. In addition, we investigate the near-optimal workstation location patterns (i.e., some general workstation configuration rules) in the context of both traditional and flying-V layouts. A series of experiments led to the following findings: (1) the flying-V layout can save 8∼26% of travel distance compared with the traditional layout, and the sacrifice of space use is only 2∼3% for medium or large warehouses; (2) instead of solving the optimization model, the proposed 2n rule and n+1 rule are simple and easily implemented ways to locate workstations, with travel distance gaps of less than 1.5% and 5% for traditional and flying-V layouts, respectively; and (3) the “optimal” cross-aisle angle (i.e., θ) in flying-V layout can be set as large as possible as long as the cross-aisle intersects the left or right edge of the warehouse.

Ergonomics analysis of gunner station of armoured combat vehicle (ACV)- Tank T 90S with special reference to seat, visual sighting system and musculoskeletal discomfort: A pilot study

Background: A combat vehicle is a tracked/wheeled land or amphibious vehicle, with or without armour or armament, designed for specific functions in combat or battle. It is an integrated mobile weapon platform comprising of multiple workstations having many equipment, switches, control and displays.Effectiveness of Combat vehicle and efficiency of crewin battle field depends upon the optimum design and placement of control and displays and workstation. Till date ergonomics studies on combat vehicle are limited and less reported.&#x0D; Aims and Objective: Present study was undertaken to investigate the gunner station of the combat vehicle (Tank T90 S) with special reference to seat and sighting system with respect to anthropometric dimensions of the crew members, to find out constraints, design limitations and mismatch in the existing vehicles; and the biomechanical responses (force and angles), comfort and discomfort during the vehicle operation.&#x0D; Materials and Methods: Ninety (90) healthy male gunner with mean age 35.2±8.5 years, stature 172.6±7.5 cm and weight 72.4±7.2 kg volunteered for the study. Anthropometric details of gunner crew, gunner seat dimension, sighting system, biomechanical response during operation, comfort and discomfort analysis were studied.&#x0D; Results: Gunner station sighting control handle is located below the recommended optimum vortex angle of ±15° from normal line of sight in vertical and horizontal plane. Hand grip strength decreased with increasing operation time. Reduction in grip strength of the gunner may tend to produce lag and delay of movement of barrel and swiftness of gunner may get compromised. Seat was not designed as per anthropometric dimensions of crew members.&#x0D; Conclusion: Present study clearly stated that non-accessibility and difficulty in operating the handle of Gun Control Equipment during operation. Sighting system and seat of existing tank is poorly ergonomically designed. Hand grip strength gradually decrease with increasing operation time.

Experiences from the epicenter: an observational report on converting a post anesthesia care unit to a COVID-19 intensive care unit

Experiences from the epicenter: an observational report on converting a post anesthesia care unit to a COVID-19 intensive care unit

A machine learning approach for improved shop-floor operator support using a two-level collaborative filtering and gamification features

The increasing gap in shopfloor operators’ skillset regarding advanced information and communication technologies along with workforce’s diversity require a cognitive system bridging such technical gaps in order to address evolving production demands and satisfy the human need for self-fulfillment and self-actualization at work. This study discusses on a two-level collaborative filtering approach to improve the distribution of information content provided to an operator for completing a manufacturing activity while considering his or her feedback. A prototype implementation is evaluated in a case study related to the operator’s job rotation on a shopfloor that involves multiple workstations and tasks.