Workshop Environment Research Articles

Should I Evaluate My Augmented Reality System in an Industrial Environment? Investigating the Effects of Classroom and Shop Floor Settings on Guided Assembly.

Numerous prior studies have investigated real-time assembly instructions using Augmented Reality (AR). However, most such experiments were conducted in laboratory settings with simplistic assembly tasks, failing to represent real-world industrial conditions. To ascertain to what extent results obtained in a laboratory environment may differ from studies in actual industrial environments, we carried out a user study with 32 manufacturing apprentices. We compared assembly task execution results in two settings, a classroom and an industrial workshop environment. To facilitate the experiments, we developed AR-guided manual assembly systems for simple and more complex assets. Our findings reveal a significantly improved task performance in the industrial workshop, reflected in faster task completion times, fewer errors, and subjectively perceived higher flow. This contradicted participants' subjective ratings, as they expected to perform better in the classroom environment. Our results suggest that the actual manufacturing environment is critical in evaluating AR systems for real-world industrial applications.

Digital twin-enhanced robotic system for remote diesel engine assembly defect inspection

Purpose This study aims to streamline and enhance the assembly defect inspection process in diesel engine production. Traditional manual inspection methods are labor-intensive and time-consuming because of the complex structures of the engines and the noisy workshop environment. This study’s robotic system aims to alleviate these challenges by automating the inspection process and enabling easy remote inspection, thereby freeing workers from heavy fieldwork. Design/methodology/approach This study’s system uses a robotic arm to traverse and capture images of key components of the engine. This study uses anomaly detection algorithms to automatically identify defects in the captured images. Additionally, this system is enhanced by digital twin technology, which provides inspectors with various tools to designate components of interest in the engine and assist in defect checking and annotation. This integration facilitates smooth transitions from manual to automatic inspection within a short period. Findings Through evaluations and user studies conducted over a relatively long period, the authors found that the system accelerates and improves the accuracy of engine inspections. The results indicate that the system significantly enhances the efficiency of production processes for manufacturers. Originality/value The system represents a novel approach to engine inspection, leveraging robotic technology and digital twin enhancements to address the limitations of traditional manual inspection methods. By automating and enhancing the inspection process, the system offers manufacturers the opportunity to improve production efficiency and ensure the quality of diesel engines.

Dynamic scheduling of workshop resource in cloud manufacturing environment

In the cloud manufacturing environment, workshop resource scheduling serves as a pivotal component, characterized by increased dynamics and complexities. Nevertheless, existing dynamic scheduling methods are often limited to solving specific dynamic events. Thus, considering the actual workshop resource scheduling in a cloud manufacturing environment, this article examines the methods to address unexpected events including randomly arriving tasks, resource breakdown, as well as resource maintenance. Besides, a dynamic scheduling method based on the Game Theory, considering workshop capacity in cloud manufacturing, was developed. In the first place, the priority of workshop tasks was evaluated by Game Theory, and the optimal task processing sequence in the workshop was determined to maximize benefits. Secondly, to verify the dynamic regulation performance of the method, it was combined with the particle swarm optimization (PSO) algorithm considering multi-objective factors to obtain an ameliorated PSO algorithm addressing the challenge of resource optimization scheduling in a genuinely dynamic workshop environment. Finally, this method was tested through a case study, and the results demonstrate that it can achieve superior dynamic and static performance compared to alternative algorithms.

Impact of 6S (5S+Safety) Implementation in Machine Workshops on Occupational Safety

In this current study, the impact of implementing 6S (5S+Safety) in the machining industry on occupational safety was investigated by selecting the chip machining section of a factory producing flywheels. To facilitate the comparison of risk levels before and after the implementation of 6S, a Fine-Kinney risk evaluation was conducted in the sawdust department before the application of 6S. The 6S implementation process took 28 days, and subsequently, a Fine-Kinney risk evaluation was performed in the sawdust department, revealing a 77.4% reduction in risks. As a result, the 77.4% reduction in accident risks indicates that the implementation of 6S, which emphasizes safety within the framework of the 5S principles, leads to a more organized, cleaner, and safer machine workshop environment. We can indicate that this approach not only reduces the risk of accidents but also enhances work efficiency, preventing time loss and material waste.

CP-RDM: a new object detection algorithm for casting and pouring robots

Abstract Automating the casting sector heavily relies on pivotal technology for object detection in pouring robots. A sophisticated algorithm designed to identify and locate target pouring holes in intricate casting workshops is crucial for advancing the intelligence of the casting process. However, the workshop environment for pouring is generally challenging, with uneven lighting, varying sizes of pouring holes, and significant occlusion in the target area, all impacting the accuracy of target detection tasks.
To overcome these challenges, this paper proposes enhancing the YOLOv8s algorithm for object detection in pouring robots. Firstly, to address the issue of different scales in pouring holes, a Multi-Scale Residual Channel and Spatial Information Fusion Module (MRCS) is designed to aggregate channel and spatial information, thereby enhancing the feature extraction capability of the model. The proposed enhancement is validated on the Pascal VOC dataset. Secondly, a SimAM attention mechanism is added at the end of the backbone network to focus the object detection network more on the positional region of the pouring hole. Importantly, this addition does not introduce extra parameters or computational burden to the model.
Finally, in the detection part of the model, the detection head from the RT-DETR model is introduced. This combination of real-time detection capability from YOLO and deep feature extraction capability from RT-DETR enhances the detection accuracy of the model while ensuring real-time performance. Experimental results on the updated pouring hole dataset reveal that, with only a slight increase in parameters, the proposed model achieves a 2.5% and 3.5% improvement in mAP@0.5 and F1-Score, respectively, compared to the baseline algorithm YOLOv8s. Precision (P) is enhanced by 1.8%, recall (R) by 3.5%, and PFS reaches 110, meeting the requirements for real-time pouring in pouring robots.

Establishment and application of the environment evaluation model for beneficiation plant

In order to evaluate the beneficiation plant environment in a more scientific and reasonable way, this paper took the workshop environment of the beneficiation plant as the research object. This paper divided the beneficiation plant into 7 evaluation units according to its functions. The evaluation indices are dust, noise, light environment, microclimate, benzene, toluene and xylene. This paper combines the G1 method and the entropy weight method to evaluate the weight of each evaluation index, the element extension model of the concentrator working environment is established by the element analysis method, and the matter element analysis method is used to establish an evaluation index system of a beneficiation plant in East China. The results show that the evaluation level of the breaking workshop and the auxiliary facilities are unqualified, the auxiliary facility is qualified, the culling workshop, culled yard and accessory building are medium, the screening workshop and grinding workshop are good.

A practical stakeholder-focused approach for assessing the biosecurity system in Pacific Island countries

ABSTRACT Aims: To develop a structured process for a transparent, efficient, high-level review of a low-resource biosecurity system (limited by physical infrastructure, financial, and human resources), in order to identify and prioritise key areas for future focus which could then lead to interventions, tailored by country, to improve the system. A key requirement was that the approach developed was culturally sensitive and respectful to Pasifika people within the country. Methods: Animal health and biosecurity systems need to be urgently strengthened by Pacific Island countries and territories (PICTs) if they are to respond to current and future threats. Understanding where additional resources should be allocated to maximise benefit and ensuring buy-in from PICT stakeholders are critical for uptake of any recommendations made. However, there is little available literature on reviewing biosecurity systems, particularly where there is a need for efficiency, simplicity, and cultural sensitivity. A framework was developed through initial in-person consultation between four New Zealand experts who had experience working in international animal health development and support programmes. This was followed by input from informal discussions with selected heads of agriculture in PICTs and included their experiences with previous system reviews, as well as general advice from experts in Pasifika culture. Foundational objectives included simplicity, local inclusivity, and a structured approach, which could be undertaken over a relatively short period of time. A rapid evidence assessment methodology was used to search the available literature (published and grey, search terms biosecurity, system, Pacific, animal, framework, and review used in AND/OR combinations), to establish an evidence base for other methods of biosecurity system review. The developed framework for review of biosecurity systems in low-resource PICTs was based on elements from expert elicitation frameworks, the SurF surveillance evaluation framework and the Performance of Veterinary Services tool from The World Organisation for Animal Health. Results: The developed framework involved bringing stakeholders together in a workshop environment and comprised up to 10 steps including mapping the PICT biosecurity system and exploring attributes of component activities. Understanding the system at a high level enables stakeholders to make informed recommendations on improvements to address future needs. Using the Delphi method, recommendations were then prioritised by stakeholders. Conclusions and clinical relevance: A distinctive difference flowing from the use of the needs analysis described in this process was the empowerment of PICT stakeholders to determine their own needs and priorities, rather than have these developed by external parties.

Characterization of VOCs emissions and associated health risks inherent to the packaging and printing industries in Shandong Province, China

Comprehensive volatile organic compounds (VOCs) emission control is imperative to decreasing occupational health risks and environmental impact of the packaging and printing industries. In this work, we investigated the VOCs emission characteristics and concentrations of individual contaminants generated by the packaging and printing industries, with regard to various categories, processes, and geographic regions. VOCs emissions, ozone formation potential (OFP), and associated health risks were assessed at 10 representative packaging and printing firms across several cities in Shandong Province, China. Plastic packaging enterprises had the greatest levels of unorganized VOCs emissions, consisting predominantly of oxygenated volatile organic compounds (OVOCs), followed by alkanes and halocarbons. From metal and paper packaging enterprises, OVOCs, alkanes, and aromatics were significant components of unorganized VOCs emissions. Aromatics, halocarbons, and OVOCs contributed significantly to OFP in workshops. The potential carcinogenic risk associated with VOCs in the packaging and printing industries was not significant. However, according to the findings in this study, the workshop environment may provide a comparatively elevated non-carcinogenic risk attributable to ethyl acetate, isopropanol, acrolein, 1,1,2-Trichloroethane, 1,2-Dichloropropane, and naphthalene exposure. In particular, the endocrine-disrupting and genetic toxic effects caused by benzene, toluene, styrene, and naphthalene should not be overlooked. Thus, it is essential to provide precedence to the working environment conditions of workshop laborers, while also undertaking scientific and systematic measures to mitigate the detrimental impacts of VOCs on the environment and human welfare.

Vocational didactics based on industrial teachers’ stories

Based on industrial teachers’ narrated experiences of teaching and meeting students at Swedish vocational high schools, this study will provide a definition of the concept of vocational didactics. The study is based on two central pillars: 1) the concept of vocational didactics and 2) narrative research. The concept of vocational didactics is elaborated on the basis of previous research, and stories are further described as the theoretical and methodological starting points. The results show that ten themes about vocational didactics (vocational teaching and vocational learning) emerge from the industrial teachers’ stories. The common denominator in the themes is the concept of occupation, which is related to employability as an industrial worker. The vocational didactics and its constituent themes, which are context-bound and change as a result of technological development and societal changes, are processed and discussed in relation to the workshop environment (master-apprentice tradition) and school environment. The conclusion is that vocational didactics comprises teaching and learning professional skills and enabling students to become professional practitioners in a profession and a labour market that change continuously in step with technological development and social change.

Five-Dimensional Modeling Technology for Intelligent Manufacturing Lines Oriented Towards Digital Twins

Intelligent manufacturing lines constitute a complex system characterized by the integration of multiple technologies, the intersection of various disciplines, multi-dimensional integration, and the interaction of numerous components. Currently, the internal environment of intelligent manufacturing workshops, processing technologies, and production processes all exhibit a high degree of complexity, and the diversity of underlying mechanical equipment is particularly notable. Compared to traditional manufacturing assembly lines, the process coupling between equipment in flow-type production lines is tighter and more significant. Therefore, this paper undertakes digital twin modeling of intelligent manufacturing lines from five aspects: geometry, motion, data, communication, and control. This approach aims to achieve precise and detailed mapping of the physical entity production line's processing operations.

Energy-efficient path planning for a multi-load automated guided vehicle executing multiple transport tasks in a manufacturing workshop environment.

Automated guided vehicles (AGVs) are typical intelligent logistics equipment, and path planning plays a significant role in the efficient use of AGVs. To better utilize multi-load AGVs and enhance the sustainability of the logistics process, an energy-efficient path planning model is formulated for a multi-load AGV executing multiple transport tasks in a manufacturing workshop environment, with transport distance and energy consumption (EC) serving as optimization objectives. Furthermore, a two-stage approach is proposed to solve it. In the first stage, the optimal energy-efficient paths connecting any two different nodes are acquired based on the workshop transport network expressed as a topological map. Afterward, the non-dominated sorting genetic algorithm-II is adopted in the second stage to determine the optimal execution sequence of pickup and delivery operations related to the assigned transport tasks, as well as to select the optimal path from the first stage's output information to execute each operation simultaneously. Moreover, the experimental study validates the energy-saving effect of the established model and the effectiveness of the solution method, and the factors affecting the multi-load AGV EC are analyzed.

Workshop environment heterogeneity shaped the microbiome and metabolome profiles during Xiasha round of Jiangxiangxing Baijiu

Workshop with different fermentation years plays an essential role in the yield and quality of Baijiu. In actual production, the quality of base Baijiu in newly built workshop is inferior to the older one. In this study, the microbiota of workshop environment and fermentation process from two workshops namely N (ferment 2 years) and O (ferment 20 years) and flavor compounds were studied during Xiasha round. Results showed workshop O accumulated more environmental microorganisms and fungi including P. kudriavzevii, Wickerhamomyces anomalus and Saccharomyces sp mainly came from ground. Yeasts including Pichia, Cyberlindnera, Wickerhamomyces and Candida were responsible for flavor substances formation in O while Saccharopolyspora was in N. This study for the first time explored the reasons for the brewing differences among N and O workshop from perspectives of workshop environment, microbial community and flavor substances, providing new ideas for guiding production as well as improvement of Baijiu quality.

Metrological characterisation of tool pre-setting optical systems based on 2D imaging

Accurate tool geometry is vital in modern computer numerical control machine tools for ensuring the accuracy of the manufactured parts in machining processes. The tool pre-setting optical systems play an important role by establishing accurate, efficient, and repeatable tool data for cutting tools varying from macro to micro size tools. The tool data is later utilised by the numerical control programs to accomplish precision machining operations with the required accuracy. However, the traceability of tool pre-setting optical systems is not guaranteed due to the lack of specific international standards, and there is a strong need of establishing a traceable measurement process which requires calibrated reference artefacts. In this work, we have established the metrological characteristics of an image-based tool pre-setting optical system based on ISO 15530 part 3. For this purpose, an artefact with sharp cutting edges was manufactured from a calibrated cylindrical gauge pin, measured on a coordinate measuring machine by two different approaches, and the impact of the edge radius is incorporated in the measurement process. The artefact was later employed in the performance verification of the optical system for on-machine tool characterization analogous to the production workshop environment, and the measured outcome of the optical sensor was evaluated with the developed metrological approaches. Experiments have shown the applicability of the measurement procedures and the relevance of the proposed reference artefact for the characterisation of image-based tool pre-setting optical systems.

Maintenance architecture design of equipment operation and maintenance system based on digital twins

The digital twins process of equipment operation and maintenance involves massive data and complex business logic. Through data awareness of equipment and workshop environment. According to the characteristics of equipment operation and maintenance, the data characteristics and requirements are analysed, an equipment operation and maintenance management system based on the micro-service framework is proposed, a set of equipment operation and maintenance digital twins are designed and a general reference software architecture is designed and by checking the underlying in-heap pattern reduces high-impact portions of memory to provide accurate follow-up complex digital twins modelling provides the architectural foundation.

Optimization of transport constraints and quality of service for joint resolution of uncertain scheduling and the job-shop problem with routing (JSSPR) as opposed to the job-shop problem with transport (JSSPT)

To better meet the qualitative and quantitative requirements of customers or relevant sector managers, workshop environments are implementing increasingly complex task management systems. The job shop scheduling problem (JSSP) involves assigning each task to a single machine while scheduling many tasks on different machines. Finding the best scheduling for machines is one of the challenging optimizations of difficult non-deterministic polynomial (NP) time problems. The fundamental goal of optimization is to shorten the makespan (total execution time of all tasks). This paper is interested in the joint resolution of scheduling and transport problems and more particularly the Job-shop problem with Routing (JSSPR) as opposed to the Job-shop problem with Transport (JSSPT). These two problems are modeled in the form of a disjunctive graph. For the JSSPT, the solution to the transport problem is not linked to any quality of service (QoS) criterion and the solution is therefore often semi-active. The Job-shop with Routing explicitly considers transport operations and uses algorithms from the transport community to solve the transport problem. It is shown that the routing part of the JSSPR is a problem of the vehicle routing family and of the Pickup and Delivery Problem family. QoS in the JSSPR is defined by the duration of tours, the duration of transport of parts and the waiting time for them. A new evaluation function – named Time-Lag Insertion Heuristic (TLH) – is proposed to evaluate a disjunctive graph by simultaneously minimizing the makespan and maximizing the quality of service. Thus, the solution obtained is not semi-active, but a compromise between the different criteria. This evaluation function is included in a metaheuristic. Our numerical evaluations demonstrate that, on the one hand, the TLH evaluation can find almost optimal solutions regarding the QoS criterion; and on the other hand, the TLH evaluation is not very sensitive to the order of insertion of the maximum time-lags during the different minimization steps.

Engineering workshop education and supervision: AR for machine operation guidance and safety instructions

This research explores the implementation of Augmented Reality (AR) in the mechanical workshop of an engineering education program. The objective is to provide engineering students with an immersive and interactive learning experience, improving their understanding of machine operation while emphasizing safety protocols. This research introduces an AR approach designed to overcome challenges when comprehending the intricate workings of machines and adhering to safety guidelines. By overlaying digital information onto the physical workspace, AR assists students in visualizing machine components, operational procedures, and safety measures, promoting a more effective learning process. In the AR experience, we incorporate sensor data from the workshop environment. This integration enables real-time monitoring of machine performance, environmental conditions, and student activities. Furthermore, the study investigates the potential of AR for workshop supervision. Workshop operators can monitor students’ activities in real-time, ensuring compliance with safety protocols and providing personalised assistance when needed.

Analysis of Potential Hazards Using the HIRADC Approach and Methods Job Safety Analysis on The Practical Process at The Department of Environmental Health

The Physics, Industrial Sanitation, and Occupational Safety Laboratory, also known to be the Health Department's Workshop Environment at the Ministry of Health Jakarta II Health Polytechnic, is part of the laboratory standards established through the Decree of the Minister of Health Number: HK.03.05/IV/14354.I/2010 concerning Health Personnel Education Laboratory Standards. To keep up with service standards or Standard Operating Procedures (SOP) in a laboratory and follow the Occupational Health and Safety management system following PP No. 50 of 2012 concerning the Implementation of Occupational Safety and Health Management Systems, the supporting facilities and infrastructure therefore require more effective and efficient attention. The objective of this study is to implement the Job Safety Analysis (JSA) and the HIRADC method to evaluate potential health and safety hazards at the Jakarta II Health Polytechnic Workshop. The result based on analysis and discussion using the JSA approach of the risk level research at the Department of Environmental Health workshop showed that 11% had a high-risk level, 28% had a medium-risk level, and 61% had a low-risk level. The highest risk is in the practical work of making slabs and testing insecticides for open joints using fogging and insecticides. The control provided is based on a control hierarchy, and it entails providing enough complete PPE in accordance with the risk of hazard and supervising the use of PPE during preparation and until the practicum process is complete.

Kaedah Menterjemah Unsur Alam Semulajadi Menjadi Karya Seni Dua Dimensi Dalam Projek Reka Bentuk Seni Bina Tahun Satu di UKM

The Architecture Design Course 1 (KKSB1116) is the main subject course for the Bachelor of Architecture Science (BSc Arch) program at Universiti Kebangsaan Malaysia (UKM). This course is offered in the first semester of year one and it is fundamental to the process of producing architectural design. The application of an experimental learning style is one of the ways to build awareness, knowledge and skills in the design learning process. This paper investigates the experiential learning style applied in the project of translating elements of nature into a self-portrait artwork using basic principles of design which are the lines and basic shapes of geometry. In this project, students were exposed to various learning methods such as experiential trip in nature, the use of sketch method in the form of mind map and the workshop environment. The research methodologies used are the combination of qualitative and quantitative approaches, where qualitative (in-depth interview and unstructured observation) is the main method. The findings showed that the students successfully translated objects from the elements of nature into the design project. It can be seen through a sketch of a graphic mind map and the production of a two-dimensional artwork design that highlights the basic principles of geometric design from a multidirectional combination of line sketches. This method of learning can be the benchmark for first year (basic) architectural education program especially for a bachelor of sciences level. The study suggests how the concept of the mind map approach and skills of workshop can be developed for the following year that is adapted to the program complexity.

Obstacle Avoidance for Automated Guided Vehicles in Real-World Workshops Using the Grid Method and Deep Learning

An automated guided vehicle (AGV) obstacle avoidance system based on the grid method and deep learning algorithm is proposed, aiming at the complex and dynamic environment in the industrial workshop of a tobacco company. The deep learning object detection is used to detect obstacles in real-time for the AGV, and feasible paths are generated by the grid method, which ultimately finds an AGV obstacle avoidance solution in complex dynamic environments. The experimental results showed that the proposed system can effectively identify and avoid obstacles in a simulated tobacco production workshop environment, resulting in the average obstacle avoidance success rate of 98.67%. The transportation efficiency of cigarette factories is significantly improved with the proposed system, reducing the average execution time of handing tasks by 27.29%. This paper expects to provide a reliable and efficient solution for AGV obstacle avoidance in real-world industrial workshops.

A multi-agent double Deep-Q-network based on state machine and event stream for flexible job shop scheduling problem

With the industry's rapid shift to large-scale personalized development, the need for a ramose multi-agent system capable of flexible job shop scheduling problem (FJSP) is apparent. As such, this paper proposes a novel framework that transforms the combinatorial optimization problem into a multi-stage sequence decision problem and introduces a multi-agent double Deep-Q-network algorithm (MADDQN) for FJSP. The event-driven workshop environment model based on state machine and event stream mechanism is constructed to transform FJSP into a Markov Decision Process (MDP) with more robust general performance and decouple the workshop environment model from the decision analysis model. The developed multi-agent reinforcement learning consisting of job agents and machine agents applies dispatching rules to maximize the cumulative reward of all agents by Boltzmann exploitation to avoid the local optimum. Results of numerical experiments reflect that the proposed MADDQN performs better than the traditional approaches in large-scale instances, and the real-time performance of the scheduling decision is guaranteed.