Design Of Manufacturing Systems Research Articles

A mixed-integer programming formulation for optimizing the double row layout problem

The Double Row Layout Problem (DRLP) asks for an arrangement of machines on both sides of a straight line corridor so as to minimize the total cost for transferring materials among machines. The DRLP is NP-Hard and has practical relevance, specially in manufacturing systems design. In this paper, we drastically reduce the time required to solve the problem by constructing a new and effective mixed-integer linear programming (MILP) model of the DRLP. The new model was obtained by reformulating an existing MILP model. This includes tightening some constraints, introducing new variables, implementing constraints to link the new and original variables; and adding valid inequalities and a valid system of equations. To reduce the size of the reformulated model, we eliminate several of the new introduced variables by a substitution using the system of equations. The computational results demonstrate that the proposed model requires considerably smaller computational times compared to the ones in the literature. As a consequence, optimal solutions can now be efficiently found for larger instances of the problem. Previous studies have been able to optimally solve, within reasonable time, instances with size up to 16 machines, while with the new model four instances with 20 machines could be optimally solved.

Utilization of Immersive Virtual Reality as an Interactive Method of Assignment Presentation

Virtual reality is a technology with many possible uses and ways to improve various processes, including the presentation of results. This paper deals with the utilization of virtual reality as a tool for assignment presentation. During the classes of manufacturing and assembly systems design, the conventional form of presentation was replaced with immersive virtual reality, where the students would present their work while wearing the virtual reality headset and walking around the 3D model of their design. The main goal was to test whether this approach had a positive impact on the students’ motivation and engagement in the presentation creation and presenting itself. To test this approach, a small case study took place at the Department of Industrial Engineering, Faculty of Mechanical Engineering at the University of Žilina. In conclusion, the overall responses to this experiment were positive; the majority of the students felt more comfortable while presenting and more motivated to put more effort into their preparation. Wearing a virtual reality headset caused the students not to have to directly face the audience, giving them more confidence while presenting. Additionally, the novelty of the virtual reality technology made the students more engaged in showing their work. There is a plan to integrate the virtual reality presentation as the stable part of this assignment.

Development of ZTA (80% Al2O3/20% ZrO2) pre-sintered blocks for milling in CAD/CAM systems

The present work aims to develop a production method of pre-sintered zirconia-toughened-alumina (ZTA) composite blocks for machining in a computer-aided design and computer-aided manufacturing (CAD-CAM) system. The ZTA composite comprised of 80% Al2O3 and 20% ZrO2 was synthesized, uniaxially and isostatically pressed to generate machinable CAD-CAM blocks. Fourteen green-body blocks were prepared and pre-sintered at 1000 °C. After cooling and holder gluing, a stereolithography (STL) file was designed and uploaded to manufacture disk-shaped specimens projected to comply with ISO 6872:2015. Seventy specimens were produced through machining of the blocks, samples were sintered at 1600 °C and two-sided polished. Half of the samples were subjected to accelerated autoclave hydrothermal aging (20h at 134 °C and 2.2 bar). Immediate and aged samples were characterized by scanning electron microscopy (SEM) and X-ray diffraction (XRD). Optical and mechanical properties were assessed by reflectance tests and by biaxial flexural strength test, Vickers indentation and fracture toughness, respectively. Samples produced by machining presented high density and smooth surfaces at SEM evaluation with few microstructural defects. XRD evaluation depicted characteristic peaks of alpha alumina and tetragonal zirconia and autoclave aging had no effect on the crystalline spectra of the composite. Optical and mechanical evaluations demonstrated a high masking ability for the composite and a characteristic strength of 464 MPa and Weibull modulus of 17, with no significant alterations after aging. The milled composite exhibited a hardness of 17.61 GPa and fracture toughness of 5.63 MPa m1/2, which remained unaltered after aging. The synthesis of ZTA blocks for CAD-CAM was successful and allowed for the milling of disk-shaped specimens using the grinding method of the CAD-CAM system. ZTA composite properties were unaffected by hydrothermal autoclave aging and present a promising alternative for the manufacture of infrastructures of fixed dental prostheses.

Development of Cyber Physical System Based Manufacturing System Design

Cyber Physical System (CPS) is Informatics and computer science. Cyber physical manufacturing system is a new research field. In the fields of computer science and manufacturing science and technology Promote the Fourth Industrial Revolution known as Industry 4.0. CPS is generally focused. About the integration of the physical world and cyberspace. It`s the integration of communication, Computational, control, and physical elements. Currently, CPS is Science, government and industry. Systematic literature review on cyber. The physical system of the manufacturing system is not available. The purpose of the chapters in this bookis to gain insight into manufacturing systems and develop cyber-physical systems. Physical systems for intelligent manufacturing. CPS is written using the concept of CPS. A 5-tier architecture system for manufacturing systems. Continuous Key Release. It also describes the technology of cyber physical manufacturing systems. Combined with manufacturing, CPS enables intelligent manufacturing and provides technical support for manufacturing upgrades and conversions. This can be summarized in three aspects: internet-based manufacturing, process intelligence, and product intelligence. Future manufacturing is said to be personalized manufacturing based on cyber physical systems, intelligent manufacturing, digital manufacturing, and network-based manufacturing. CPS continues to transform the manufacturing trends of the industry, creating even more amazing value for future global manufacturing scenarios

Verifying the seating of a 3D-printed removable die using elastomeric matrices: A dental technique.

Computer-aided design and computer-aided manufacturing systems enable digital designing and 3-dimensional (3D) printing of definitive casts with removable dies. However, the fit of the removable dies should be without interferences for their accurate positioning in the cast. Given that the accuracy of additive manufacturing depends on design- and manufacturing-related factors, verifying the accuracy of the position of 3D-printed removable dies in their cast is essential to fabricate positionally accurate definitive prostheses, which would enable minimal or no laboratory and clinical adjustments. This dental technique article presents a straightforward approach to verify the seating of a 3D-printed removable die by using verification matrices made of a polyvinylsiloxane interocclusal registration material.

Facility layout planning through the ALDEP Method in the wooden cable reels industry

Facility layout planning plays a pivotal role in manufacturing system design, impacting vital metrics such as lead time, handling costs, and space optimization. While a significant portion of research has been invested in refining existing facility layouts, there is a noticeable research gap in devising optimized layouts for new establishments, especially in the value-added wood products domain. Addressing this lacuna, this research focused on designing an efficient department-level layout for a wooden cable drums manufacturing facility in an area of 4150 m2. This facility included both office and production areas. The investigative process was segmented into four distinct phases: Deciding the strategic positioning of the facility on the available plot, defining the functional and spatial requirements for each department, establishing the intricate relationship dynamics between these individual units, and rigorously documenting the most optimal department-level facility layout. For precision in layout creation, the ALDEP algorithm was employed, which was further visualized to offer a comprehensive three-dimensional representation. The final layout seamlessly organized seven departments within the 1st Floor Office Area, eight in the 2nd Floor Office Area, and thirteen within the Production Floor. Efficiency evaluation of these areas yielded scores of -811, 184, and -318, respectively. Conclusively, this research furnished actionable insights for manufacturers within the wood products sector and was expected to be an invaluable reference for academics delving into facility planning and value-added wood products manufacturing.

A Framework for Sustainable Manufacturing: Integrating Industry 4.0 Technologies with Industry 5.0 Values

The limitations imposed by resource scarcity and the imperative to mitigate adverse environmental and societal impacts have intensified the urgency of developing more sustainable manufacturing systems. Simultaneously, the rapid development and implementation of new technologies is exacerbating the digital divide among vulnerable workers. Concomitantly, the enabling technologies stemming from Industry 4.0 offer significant potential to enhance the competitiveness of manufacturing systems. However, the impact of these enabling technologies on achieving sustainable manufacturing remains uncertain. This paper embarks on a comprehensive exploration to address this knowledge gap. Initially, it assesses the suitability of each enabling technology within Industry 4.0 across the economic, social, and environmental dimensions of sustainability. Subsequently, the needs of the production process are studied to characterize its sustainable performance. For this, the ASTM E3012-22 standard is introduced. Building upon this foundation, the incorporation of Industry 5.0 is introduced to guide the selection of enabling technologies for sustainability based on its core values, encompassing sustainability, human-centricity, and resilience. The integration of new technologies guided by these values can help bridge the technological divide among vulnerable workers. Finally, a theoretical framework is proposed to enable the design of sustainable manufacturing systems guided by Industry 5.0 values. This framework enables the seamless integration of enabling technologies, machinery, and human expertise throughout the system life cycle.

Data-driven hybrid algorithm with multi-evolutionary sampling strategy for energy-saving buffer allocation in green manufacturing

Buffer allocation, which is an important research topic in manufacturing system design, typically focuses on system performance and cost. However, few previous studies have been performed to investigate energy-saving buffer allocation, which can decrease operational energy consumption in green manufacturing. Furthermore, the computational efficiency of solving the buffer allocation problem requires further investigation. This paper proposes a data-driven hybrid algorithm based on multi-evolutionary sampling strategies for solving energy-saving buffer allocation that can maximize the throughput rate and minimize energy consumption. Two evolutionary sampling strategies, that is, global search and surrogate-assisted local search, are integrated to balance exploitation and exploration. In addition, a database containing historical data pertaining to buffer allocation solutions is used to develop surrogate models that can rapidly predict the throughput and energy consumption and improve the evaluation efficiency of the local search strategy. Experimental results demonstrate the efficacy of the proposed algorithm. This study contributes to an efficient buffer allocation and presents a new perspective on energy-saving measures for green manufacturing designs.

Multi-agent cooperative swarm learning for dynamic layout optimisation of reconfigurable robotic assembly cells based on digital twin

AbstractTo meet the requirement of product variety and short production cycle, reconfigurable manufacturing system is considered as an effective solution in addressing current challenges, such as increasing customisation, high flexibility and dynamic market demand. Dynamic factory layout design and optimisation are the crucial factors in response to rapid change in the mechanical structure, software and hardware integration, as well as production capability and functionality adjustment. Nevertheless, in the current research, the layout design for reconfigurable manufacturing systems is usually simplified with autonomous devices being regarded as 2D shapes. Issues such as overlapping and transportation distance are also addressed in an approximate form. In this paper, we present a novel multi-agent cooperative swarm learning framework for dynamic layout optimisation of reconfigurable robotic assembly cells. Based on its digital twin established in the proposed learning environment (constructed in Visual Components and controlled by TWINCAT), the optimisation framework uses 3D digital representation of the facility models with minimal approximation. Moreover, instead of using a traditional centralised learning manner, multi-agent system could provide an alternative way to address the layout issues combined with the proposed decentralised multi-agent cooperative swarm learning. In order to verify the application feasibility of the learning framework, two aerospace manufacturing use cases were implemented. In the first use case, the layout compactness is reduced by 3.8 times compared with the initial layout setting, the simulated production time is reduced by 2.3 times, and the rearrangement cost decreased by 33.4$$\%$$ % . In addition, all manufacturing activity within the cell can be achieved with a feasible robot path, meaning without any joint limits, reachability or singularity issue at each key assembly point. In the second use case, we demonstrated that with the proposed dynamic layout optimisation framework, it is possible to flexibly adjust learning objectives by selecting various weight parameters among layout compactness, rearrangement cost and production time.

A comparative evaluation of physical properties of CAD/CAM complete denture resins- an in vitro study

BackgroundIn dentistry, there is a growing preference for computer-aided design and computer-aided manufacturing (CAD/CAM) systems over traditional laboratory procedures. However, there is not much literature comparing various CAD/CAM materials. Thus, this study aimed to assess and compare the color stability and hardness of gingival and tooth colored milled and 3D-printed acrylic resins.Materials and methodsFour types of CAD/CAM materials were prepared: 3D-printed pink shade (PP), milled polymenthymethacrylate (PMMA) pink shade (MP), 3D-printed tooth shade (PT) and milled PMMA tooth shade (MT) (n = 6). For hardness, disc shaped samples of 15 mm × 2 mm and for color stability, bar shaped samples of 65mmx10mmx2.5 mm were prepared and polished. Vickers hardness test was performed in a microhardness tester. Color stability test was done by immersing in coffee solution and coca cola for 7 days. Day 0 and day 7 measurements were recorded using a digital spectrophotometer and the change in color was calculated. For statistical analysis, one-way ANOVA and Tukey’s post hoc tests were done.ResultsFor color stability, milled PMMA was superior to 3D-printed resin samples. Milled pink and tooth shade samples had similar color stability, whereas 3D-printed tooth shade samples were more color stable as compared to pink shade 3D-printed samples. For hardness, milled tooth shade PMMA was the most superior one, followed by 3D-printed tooth shade, whereas pink shade milled PMMA and 3D-printed resin samples had similar hardness values and were inferior to the tooth shade CAD/CAM materials.ConclusionColor stability of milled PMMA is superior to that of 3D-printed resins. Hardness of tooth shade milled and 3D-printed resins is more than that of pink shade milled and 3D-printed resins.

Cell formation and layout design using genetic algorithm and TOPSIS: A case study of Hydraulic Industries State Company.

Cell formation (CF) and machine cell layout are two critical issues in the design of a cellular manufacturing system (CMS). The complexity of the problem has an exponential impact on the time required to compute a solution, making it an NP-hard (complex and non-deterministic polynomial-time hard) problem. Therefore, it has been widely solved using effective meta-heuristics. The paper introduces a novel meta-heuristic strategy that utilizes the Genetic Algorithm (GA) and the Technique of Order Preference Similarity to the Ideal Solution (TOPSIS) to identify the most favorable solution for both flexible CF and machine layout within each cell. GA is employed to identify machine cells and part families based on Grouping Efficiency (GE) as a fitness function. In contrast to previous research, which considered grouping efficiency with a weight factor (q = 0.5), this study utilizes various weight factor values (0.1, 0.3, 0.7, 0.5, and 0.9). The proposed solution suggests using the TOPSIS technique to determine the most suitable value for the weighting factor. This factor is critical in enabling CMS to design the necessary flexibility to control the cell size. The proposed approach aims to arrange machines to enhance GE, System Utilization (SU), and System Flexibility (SF) while minimizing the cost of material handling between machines as well as inter- and intracellular movements (TC). The results of the proposed approach presented here show either better or comparable performance to the benchmark instances collected from existing literature.

A practical simulation approach for the support of wire arc DED additive manufacturing systems design

Wire Arc Directed Energy Deposition (DED) is a subcategory of the DED Additive Manufacturing (AM) technology that is rapidly gaining popularity due to its potential to produce large-scale, complex metal parts while maintaining a lower cost and higher productivity and sustainability when compared with other AM technologies. Additionally, Wire Arc DED permits a high level of customization in terms of designing and implementing manufacturing systems. However, there are still important quality issues hindering wire Arc DED, along with limited simulation approaches that offer the necessary practicality, from an industrial perspective, to support the design of wire Arc DED manufacturing systems. Towards this goal, aiming to the minimization of the experimental cost and time, a simulation approach of wire arc DED is presented in this study. The model has been developed in COMSOL Multiphysics, allowing for a high level of customization, while maintaining practicality and ease of use, both in terms of implementation as well as computational cost. The modeling approach is analyzed, followed by the implementation of the methodology in a case study. Preliminary results are presented, discussed, and accompanied by suggestions for future research.

Design and implementation of intelligent manufacturing system based on sensor networks and cloud computing technology

Design and implementation of intelligent manufacturing system based on sensor networks and cloud computing technology

Design of multi-arc collaborative additive manufacturing system and forming performance research

In view of the key issue of high-quality wire-arc-additive-manufacturing (WAAM) of large metal components, this paper has devised a suite of multi-arc collaborative additive manufacturing equipment endowed with functionalities for controlling arc behavior, managing melt pool dimensions, conducting 3D measurements, and executing subtractive machining. In the initial phase, a cutting-edge five-arc additive manufacturing head apparatus was meticulously engineered. This apparatus ingeniously blends two single-wire torches augmented by three-wire oscillating torches, synergizing deposition metal performance and forming effective. Subsequently, extensive research was carried out to explore a master-slave control-based method for orchestrating the synchronized movements of multiple robotic entities. This diligent investigation culminated in the seamless integration of a multi-arc collaborative additive manufacturing equipment, comprising five-arc high-efficiency additive units, a 3D measurement module, and a precision-driven subtractive machining unit. The influence of different horizontal distances between arc guns on the temperature field and mechanical properties of components was investigated through process experiments. The research results indicate that as the horizontal spacing between the arc guns increases, the cooling rate of the deposited metal gradually slows down, leading to an extended period of elevated temperatures. As a result, both tensile strength and yield strength gradually decrease, while elongation and impact absorption capacity first increase and then decrease. In the end, the developed equipment was utilized to fabricate large ship propeller bracket components, achieving a remarkable 4.7 times increase in manufacturing efficiency compared to single-arc additive manufacturing.

Concurrent Value-Driven Decision-Making Process for the Aircraft, Supply Chain and Manufacturing Systems Design

The integration of product design and supply-chain management can lead to an increase in the profitability and efficiency of companies. However, considering manufacturing, supply chain, and aircraft criteria in the early design phase increases the size of the solutions’ trade space and, thus, the complexity of performing the decision-making process. This paper demonstrates how to leverage value-model theory to simplify the decision-making process when multiple criteria related to multiple systems are considered at the same time. The proposed concurrent approach is formalized from a systems-engineering perspective, considering the interactions between the lifecycle stages of the System of Interest, i.e., the aircraft, and Enabling Systems like the supply chain and manufacturing. A value-based interactive dashboard, called VALORISE, is developed to automatize the process, support decision-makers in modeling their expectations, analyze real-time strategic scenarios, and easily explore the value-driven trade space for best-solution identification. An aeronautical application case highlights the advantages of leveraging the proposed concurrent approach to overcome the limits of traditional approaches, in which decisions about supply chain and manufacturing are addressed once the aircraft configuration is decided.

A framework to design smart manufacturing systems for Industry 5.0 based on the human-automation symbiosis

ABSTRACT The concept of Industry 5.0 (I5.0) promotes the human-centricity as the core value behind the evolution of smart manufacturing systems (SMSs), based on a novel use of digital technologies in the design and management of modern industrial systems to take up the socio-technical challenges. In this context, the paper proposes a Smart Manufacturing Systems Design (SMSD) framework enabling I5.0, based on the human-automation symbiosis. Thanks to an ‘Augmented Digital Twin’ (ADT) able to integrate and digitize all the entities of the factory (i.e. machines, robots, environments, interfaces, people), AI-driven applications can be built to support the user domain and make people and machines co-evolve thanks to a systematic data sharing between physical and digital assets (e.g. digital twin, virtual mock-ups, human-machine interfaces), optimizing factory productivity and workers wellbeing. In this framework, machines and humans can both generate knowledge and learn from each other, generating a virtuous co-evolution, supporting the understanding of the human-machine interplay and the creation of an effective collaboration between people and SMSs. The framework was conceived and validated involving four industrial companies, belonging to diverse sectors, interested in overcoming the current limits of I4.0 lines by including the human factors for future SMS management.

Manufacturing System Design in Industry 5.0: Incorporating Sociotechnical Systems and Social Metabolism for Human-Centered, Sustainable, and Resilient Production

This paper delves into the concept of social metabolism as a foundation for the development of sociotechnical systems in Industry 5.0. The study conducts an analysis of the existing methods and approaches for designing sociotechnical systems, and reviews publications that utilize such systems to incorporate Industry 4.0 technologies into manufacturing processes. Additionally, it examines the three key factors of Industry 5.0 and the enabling framework of Industry 4.0 technologies. Based on these investigations, a theoretical model is proposed for manufacturing system design, employing sociotechnical systems to integrate Industry 4.0 enabling technologies, while considering the essential aspects of Industry 5.0. The model emphasizes the early consideration of sociotechnical systems to design manufacturing systems that prioritize human-centricity, sustainability, and resilience. By embracing this comprehensive approach, the proposed model contributes to the realization of a production environment aligned with societal needs, fostering a more conscious and adaptable industry.

Manufacturing system reconfiguration towards sustainable production: a novel hybrid optimization methodology.

Developing a sustainable manufacturing system is a progressively challenging issue as governments across the world have been enforcing increasingly severe regulations by promoting the reduction of environmental waste for manufacturing and energy-saving production activities. Thus, there is a need for developing a sustainable manufacturing system that can be fully examined by incorporating ecological aspects (e.g., consumed energy) for related operations of a manufacturing system using computer-based discrete event simulation tools. In this study, a combined framework of a novel hybrid fuzzy multi-objective optimization and discrete event simulation approach is presented. We combine ecological and economic data and optimization techniques that are aimed at minimizing economic and ecological objectives in a manufacturing system at an early design phase. Hence, the fuzzy multi-objective optimization model is formulated by incorporating economic and ecological parameters. Again, the discrete event simulation model is established based on a comprehensive performance evaluation of the production system. This study also supports design decisions in determining optimum machine numbers, lighting, and cooling equipment required for the production processes within the sustainable manufacturing in conjunction with the most effective level of material flows. In addition, an integrated Decision-Making Trial and Evaluation Laboratory (DEMATEL)-epsilon constraint approach is applied to handle the multiple-objective optimization problem towards a set of trade-offs among the optimization objectives. A real-life application is carried out for investigating the applicability of the created hybrid framework. The findings of this study demonstrate that this framework is useful as a decision-making tool since it can develop a sustainable manufacturing system design considering an optimal solution associated with amounts of energy usage and CO2 emissions under economic constraints.

A multi-objective flexible manufacturing system design optimization using a hybrid response surface methodology

The present study proposes a hybrid framework combining multiple methods to determine the optimal values of design variables in a flexible manufacturing system (FMS). The framework uses a multi-objective response surface methodology (RSM) to achieve optimum performance. The performance of an FMS is characterized using various weighted measures using the best–worst method (BWM). Subsequently, an RSM approximates the functional relationship between the FMS performance and design variables. The central composite design (CCD) is used for this aim, and a polynomial regression model is fitted among the factors. Eventually, a bi-objective model, including the fitted and cost functions, is formulated and solved. As a result, the optimal percentage for deploying the FMS equipment and machines to achieve optimal performance with the lowest deployment cost is determined. The proposed framework can serve as a guideline for manufacturing organizations to lead strategic decisions regarding the design problems of FMSs. It significantly increases productivity for the manufacturing system, reduces redundant labor and material handling costs, and facilitates production.

Specifying task allocation in automotive wire harness assembly stations for Human-Robot Collaboration

Wire harness assembly is normally a manual assembly process that poses ergonomic challenges. As a consequence of the rapidly expanding electrification of vehicles and transportation systems, the demand for wire harnesses can be expected to grow radically, further increasing assembly operator challenges. Thus, automating this assembly process is highly prioritised by production engineers. The rapid development of industrial robot technology has enabled more human-robot collaboration possibilities, simplifying the automation of wire harness process tasks. However, successful automation applications involving humans require efficient and safe allocation of tasks between humans and technology. Unfortunately, present assembly system design methods may be obsolete and insufficient in light of the capabilities of emerging automation technologies such as collaborative robots. This paper presents a design and specification methodology for human-centred manufacturing systems and focuses on collaborative assembly operations in complex production systems. A case study on human-robot collaboration provides an application example from a wire-harness collaborative assembly process. The proposed design methodology combines hierarchical task analysis with assessments of cognitive and physical Levels of Automation (LoAc and LoAp). The assessments are then followed by evaluations of the Levels of human-robot Collaboration (LoC) and the Levels of operator Skill requirements (LoSr) respectively. A task allocation matrix supports the identification of possible combinations of automation and collaboration solutions for a human-centred and collaborative wire harness assembly process. System designers and integrators may utilise the design and specification methodology to identify the potential and extent of human-robot collaboration in collaborative manufacturing assembly operations.