Design fixation, which is a form of cognitive bias, is commonly reported to unconsciously occur when designers take the path of least resistance during the fulfillment of a design task. It’s thought to be easy and effortless. Nonetheless, the mental states such as mental effort and mental fatigue that accompany the occurrence of different levels of design fixation are still unknown. In the present study, an experiment using electroencephalography (EEG) was conducted to examine the mental effort and mental fatigue involved in the occurrence of different levels of design fixation during creative idea generation. Fluency, flexibility, the degree of copying, and the time spent generating ideas were used to evaluate the design performance and fixation level of each participant, and the task-related power changes of theta, alpha, and beta bands of participants with higher and lower levels of fixation during creative idea generation process were compared and analyzed separately. The comparison results revealed that participants with higher levels of design fixation made the less mental effort and showed higher levels of mental fatigue during the ideation process compared to those with lower levels of design fixation. These results provide additional evidence for the mental states involved in the occurrence of design fixation and could contribute to a deeper understanding of design fixation from the neuroscience perspective.
{"title":"Utilizing EEG to Explore the Mental States Involved in the Occurrence of Different Levels Design Fixation","authors":"Juan Cao, Wu Zhao, Xin Guo, Ting-Wei Wu","doi":"10.1115/detc2021-70913","DOIUrl":"https://doi.org/10.1115/detc2021-70913","url":null,"abstract":"\u0000 Design fixation, which is a form of cognitive bias, is commonly reported to unconsciously occur when designers take the path of least resistance during the fulfillment of a design task. It’s thought to be easy and effortless. Nonetheless, the mental states such as mental effort and mental fatigue that accompany the occurrence of different levels of design fixation are still unknown. In the present study, an experiment using electroencephalography (EEG) was conducted to examine the mental effort and mental fatigue involved in the occurrence of different levels of design fixation during creative idea generation. Fluency, flexibility, the degree of copying, and the time spent generating ideas were used to evaluate the design performance and fixation level of each participant, and the task-related power changes of theta, alpha, and beta bands of participants with higher and lower levels of fixation during creative idea generation process were compared and analyzed separately. The comparison results revealed that participants with higher levels of design fixation made the less mental effort and showed higher levels of mental fatigue during the ideation process compared to those with lower levels of design fixation. These results provide additional evidence for the mental states involved in the occurrence of design fixation and could contribute to a deeper understanding of design fixation from the neuroscience perspective.","PeriodicalId":23602,"journal":{"name":"Volume 2: 41st Computers and Information in Engineering Conference (CIE)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2021-08-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"75227197","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
This paper presents a novel assessment method for Systems Thinking and its supporting competencies. Systems Thinking is a key component in engineering education, providing students with the means to explore, understand, and design engineered systems both holistically and in terms of the relationships between their components, which can be both technical and non-technical. The assessment method described in this paper is implemented as a software simulation of a domain-agnostic system to support integration of Systems Thinking into engineering education. The simulation was tested with a group of beta-testers and then fully deployed online as a freely available tool for a 6-month experimental period. The pool of volunteer participants included students and mixed professionals from a diverse set of geographical, educational, and career backgrounds. Results of the assessment show success at both evaluating Systems Thinking Maturity as a whole, and at assessing complex facets of Systems Thinking that have eluded assessment in prior methods. The tool shows promise at evaluating competencies within all four Systems Thinking domains — Mindset, Content, Structure, and Behavior. These domains contain key systemic skills such as the ability to recognize interconnections and feedback loops, see non-linear causal relationships, and understand dynamic behavior. When examined holistically through multiple regression analysis, participants’ scores in the 11 assessed competencies show a moderate to high ability to predict their levels of overall Systems Thinking performance in the simulation. The results also reveal previously unknown dependencies and strengths of relationships between Systems Thinking competencies.
{"title":"Systems Thinking Assessment: A Method Through Computer Simulation","authors":"Ross Arnold, J. Wade, A. E. Bayrak","doi":"10.1115/detc2021-68180","DOIUrl":"https://doi.org/10.1115/detc2021-68180","url":null,"abstract":"\u0000 This paper presents a novel assessment method for Systems Thinking and its supporting competencies. Systems Thinking is a key component in engineering education, providing students with the means to explore, understand, and design engineered systems both holistically and in terms of the relationships between their components, which can be both technical and non-technical. The assessment method described in this paper is implemented as a software simulation of a domain-agnostic system to support integration of Systems Thinking into engineering education. The simulation was tested with a group of beta-testers and then fully deployed online as a freely available tool for a 6-month experimental period. The pool of volunteer participants included students and mixed professionals from a diverse set of geographical, educational, and career backgrounds. Results of the assessment show success at both evaluating Systems Thinking Maturity as a whole, and at assessing complex facets of Systems Thinking that have eluded assessment in prior methods. The tool shows promise at evaluating competencies within all four Systems Thinking domains — Mindset, Content, Structure, and Behavior. These domains contain key systemic skills such as the ability to recognize interconnections and feedback loops, see non-linear causal relationships, and understand dynamic behavior. When examined holistically through multiple regression analysis, participants’ scores in the 11 assessed competencies show a moderate to high ability to predict their levels of overall Systems Thinking performance in the simulation. The results also reveal previously unknown dependencies and strengths of relationships between Systems Thinking competencies.","PeriodicalId":23602,"journal":{"name":"Volume 2: 41st Computers and Information in Engineering Conference (CIE)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2021-08-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"80211695","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Grasping sheet metal objects for manufacturing operations requires custom-made robot-mounted end-effectors to grip the parts. Modern end-effectors use multi-type grasp where a combination of gripper types such as suction cups, magnets, and fingers may be used. This paper presents a genetic algorithm-based approach of grasp design automation. The algorithm first generates an option space of possible grasping locations by analyzing the geometry of the sheet metal part and then uses a genetic algorithm to optimize the grasp using up to five magnets and suction cups. The algorithm includes as fitness criteria the factor of safety of the total gripping force against part weight, the unbalanced moment created by the gripping forces and part weight, the cost of the grasp, and three combinations of these parameters. The GA features asexual reproduction, mutation, and elitism. The algorithm is implemented in the Siemens NX™ Knowledge Fusion language and on Microsoft VBA code. The paper presents detailed test results and sensitivity analyses that indicate that genetic algorithms can produce viable solutions for multi-type grasp configurations and that the algorithm behaves in response to varying its control parameters in ways that are logically anticipated.
{"title":"Evolutionary Grasp Planning for Sheet Metal Parts With Multi-Type Grippers","authors":"Jicmat Andres Ali Tribaldos, Chiradeep Sen","doi":"10.1115/detc2021-71632","DOIUrl":"https://doi.org/10.1115/detc2021-71632","url":null,"abstract":"\u0000 Grasping sheet metal objects for manufacturing operations requires custom-made robot-mounted end-effectors to grip the parts. Modern end-effectors use multi-type grasp where a combination of gripper types such as suction cups, magnets, and fingers may be used. This paper presents a genetic algorithm-based approach of grasp design automation. The algorithm first generates an option space of possible grasping locations by analyzing the geometry of the sheet metal part and then uses a genetic algorithm to optimize the grasp using up to five magnets and suction cups. The algorithm includes as fitness criteria the factor of safety of the total gripping force against part weight, the unbalanced moment created by the gripping forces and part weight, the cost of the grasp, and three combinations of these parameters. The GA features asexual reproduction, mutation, and elitism. The algorithm is implemented in the Siemens NX™ Knowledge Fusion language and on Microsoft VBA code. The paper presents detailed test results and sensitivity analyses that indicate that genetic algorithms can produce viable solutions for multi-type grasp configurations and that the algorithm behaves in response to varying its control parameters in ways that are logically anticipated.","PeriodicalId":23602,"journal":{"name":"Volume 2: 41st Computers and Information in Engineering Conference (CIE)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2021-08-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"79069437","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Both man-made and natural materials exhibit heterogeneous properties at smaller observation scales. The multiscale analysis allows the inclusion of fine-scale information in coarse-scale simulations. One of the commonly used methods is homogenization, replacing the detailed fine-scale structures with their locally homogeneous effective material properties. When fine-scale material structures are stationary, representative volume elements (RVE) are often identified for their effective material properties to be applied over the entire structure. However, in non-stationary material structures, it is inappropriate to assume a single representative material. In this case, homogenization is often required for every individual cell, resulting in significant increases in computational cost. We propose a stiffness-based clustering algorithm that reduces the total number of homogenization computations needed for multiscale analysis. Cells with similar effective stiffness tensors are clustered together such that only a single homogenization is required for each cluster. Specifically, the clustering algorithm is based on the novel concept of Eigenstiffness, which represents the relative directional stiffness of a given material structure. The rotation invariant property of Eigenstiffness allows material structure with similar intrinsic stiffness but different orientations to be clustered together, further decreasing the number of clusters required for the multiscale analysis. Without a priori knowledge of the accurate homogenized material properties, approximated elasticity tensors and Eigenstiffness estimated through FFT-based homogenization methods are used for rapid clustering. The effectiveness of the method is verified by numerical simulations on various multiscale structures, including Voronoi foams and fiber-reinforced composites.
{"title":"Fast Two-Scale Analysis via Clustering","authors":"Chongxi Yuan, Xingchen Liu","doi":"10.1115/detc2021-68633","DOIUrl":"https://doi.org/10.1115/detc2021-68633","url":null,"abstract":"\u0000 Both man-made and natural materials exhibit heterogeneous properties at smaller observation scales. The multiscale analysis allows the inclusion of fine-scale information in coarse-scale simulations. One of the commonly used methods is homogenization, replacing the detailed fine-scale structures with their locally homogeneous effective material properties. When fine-scale material structures are stationary, representative volume elements (RVE) are often identified for their effective material properties to be applied over the entire structure. However, in non-stationary material structures, it is inappropriate to assume a single representative material. In this case, homogenization is often required for every individual cell, resulting in significant increases in computational cost.\u0000 We propose a stiffness-based clustering algorithm that reduces the total number of homogenization computations needed for multiscale analysis. Cells with similar effective stiffness tensors are clustered together such that only a single homogenization is required for each cluster. Specifically, the clustering algorithm is based on the novel concept of Eigenstiffness, which represents the relative directional stiffness of a given material structure. The rotation invariant property of Eigenstiffness allows material structure with similar intrinsic stiffness but different orientations to be clustered together, further decreasing the number of clusters required for the multiscale analysis. Without a priori knowledge of the accurate homogenized material properties, approximated elasticity tensors and Eigenstiffness estimated through FFT-based homogenization methods are used for rapid clustering. The effectiveness of the method is verified by numerical simulations on various multiscale structures, including Voronoi foams and fiber-reinforced composites.","PeriodicalId":23602,"journal":{"name":"Volume 2: 41st Computers and Information in Engineering Conference (CIE)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2021-08-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"76668800","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Chen Gui, Ranyi Zeng, Kenji Takahashi, Naoki Herai, K. Aoyama
In the preliminary design of merchant ships, shipbuilders generally modify some of the standard specifications to fulfill shipowner needs, which is time-consuming owing to the complex techno-economic constraints of ship design. Therefore, an appropriate standard specifications formulation method is necessary to improve the efficiency of the preliminary design. In this study, we performed genetic algorithm-based clustering to determine the subtypes of a specific type of merchant ship and formulated the standard specification for each subtype. To demonstrate the effectiveness of the proposed method, experiments were performed using 98 specification documents to formulate the standard specifications. The results showed that feature relations among each determined subtype were significantly simpler than those of the main type; thereby, the formulated standard specifications were desirable in the preliminary design of merchant ships.
{"title":"Genetic Algorithm-Based Clustering Method to Formulate Standard Specifications for Merchant Ship Preliminary Design","authors":"Chen Gui, Ranyi Zeng, Kenji Takahashi, Naoki Herai, K. Aoyama","doi":"10.1115/detc2021-69245","DOIUrl":"https://doi.org/10.1115/detc2021-69245","url":null,"abstract":"\u0000 In the preliminary design of merchant ships, shipbuilders generally modify some of the standard specifications to fulfill shipowner needs, which is time-consuming owing to the complex techno-economic constraints of ship design. Therefore, an appropriate standard specifications formulation method is necessary to improve the efficiency of the preliminary design. In this study, we performed genetic algorithm-based clustering to determine the subtypes of a specific type of merchant ship and formulated the standard specification for each subtype. To demonstrate the effectiveness of the proposed method, experiments were performed using 98 specification documents to formulate the standard specifications. The results showed that feature relations among each determined subtype were significantly simpler than those of the main type; thereby, the formulated standard specifications were desirable in the preliminary design of merchant ships.","PeriodicalId":23602,"journal":{"name":"Volume 2: 41st Computers and Information in Engineering Conference (CIE)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2021-08-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"76893430","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Advances in additive manufacturing enable the fabrication of complex structures with intricate geometric details. It also escalates the potential for high-resolution structure design. However, the increasingly finer design brings computational challenges for structural optimization approaches such as topology optimization (TO) since the number of variables to optimize increases with the resolutions. To address this issue, two-scale TO paves an avenue for high-resolution structural design. The design domain is first discretized to a coarse scale, and the material property distribution is optimized, then using micro-structures to fill each property field. In this paper, instead of finding optimal properties of two scales separately, we reformulate the two-scale TO problem and optimize the design variables concurrently in both scales. By introducing parameterized periodic cellular structures, the minimal surface level-parameter is defined as the material design parameter and is implemented directly in the optimization problem. A numerical homogenization method is employed to calculate the elasticity tensor of the cellular materials. The stiffness matrices of the cellular structures derived as a function of the level parameters, using the homogenization results. An additional constraint on the level parameter is introduced in the structural optimization framework to enhance adjacent cellulars interfaces’ compatibility. Based on the parameterized micro-structure, the optimization problem is solved concurrently with an iterative solver. The reliability of the proposed approach has been validated with different engineering design cases. Numerical results show a noticeable increase in structure stiffness using the level parameter directly in the optimization problem than the state-of-art mapping technique.
{"title":"Two-Scale Topology Optimization With Parameterized Cellular Structures","authors":"Sina Rastegarzadeh, Jun Wang, Jida Huang","doi":"10.1115/detc2021-71980","DOIUrl":"https://doi.org/10.1115/detc2021-71980","url":null,"abstract":"\u0000 Advances in additive manufacturing enable the fabrication of complex structures with intricate geometric details. It also escalates the potential for high-resolution structure design. However, the increasingly finer design brings computational challenges for structural optimization approaches such as topology optimization (TO) since the number of variables to optimize increases with the resolutions. To address this issue, two-scale TO paves an avenue for high-resolution structural design. The design domain is first discretized to a coarse scale, and the material property distribution is optimized, then using micro-structures to fill each property field. In this paper, instead of finding optimal properties of two scales separately, we reformulate the two-scale TO problem and optimize the design variables concurrently in both scales. By introducing parameterized periodic cellular structures, the minimal surface level-parameter is defined as the material design parameter and is implemented directly in the optimization problem. A numerical homogenization method is employed to calculate the elasticity tensor of the cellular materials. The stiffness matrices of the cellular structures derived as a function of the level parameters, using the homogenization results. An additional constraint on the level parameter is introduced in the structural optimization framework to enhance adjacent cellulars interfaces’ compatibility. Based on the parameterized micro-structure, the optimization problem is solved concurrently with an iterative solver. The reliability of the proposed approach has been validated with different engineering design cases. Numerical results show a noticeable increase in structure stiffness using the level parameter directly in the optimization problem than the state-of-art mapping technique.","PeriodicalId":23602,"journal":{"name":"Volume 2: 41st Computers and Information in Engineering Conference (CIE)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2021-08-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"85898178","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
The hip muscles account for a great percentage of the total human energy expenditure during walking and many wearable devices have been developed in assisting the hip joint to reduce the metabolic Cost Of Transport (COT) for walking. However, the effectiveness of assisting the hip in only one direction (either flexion or extension) or both directions has not been systematically studied and the underlying muscle mechanics and energetics affected by the assistance are not well understood. In this study, human-exoskeleton simulation based optimizations were performed to find optimized hip assistance torque profiles for (1) unidirectional flexion assistance, (2) unidirectional extension assistance, and (3) bidirectional flexion and extension assistance. Our results show that the bidirectional assistance is the most effective in reducing the COT of walking (22.7% reduction) followed by flexion (19.2%) and extension (11.7%). The flexion assistance resulted in more COT saving than the output of its net work by 35.9%, which indicates that the negative work done (42.2% of its positive counterpart) also played an important role in reducing the COT. The bidirectional assistance also reduced the activations of the hip extensors to a great extent and shifted the activation pattern of the hip flexor (ilipsoas). These results can provide valuable information for optimal hip actuation (timing and profiles) and help exoskeleton designers make informed decisions.
{"title":"Optimized Torque Assistance During Walking With an Idealized Hip Exoskeleton","authors":"Neethan Ratnakumar, Xianlian Zhou","doi":"10.1115/detc2021-71376","DOIUrl":"https://doi.org/10.1115/detc2021-71376","url":null,"abstract":"\u0000 The hip muscles account for a great percentage of the total human energy expenditure during walking and many wearable devices have been developed in assisting the hip joint to reduce the metabolic Cost Of Transport (COT) for walking. However, the effectiveness of assisting the hip in only one direction (either flexion or extension) or both directions has not been systematically studied and the underlying muscle mechanics and energetics affected by the assistance are not well understood. In this study, human-exoskeleton simulation based optimizations were performed to find optimized hip assistance torque profiles for (1) unidirectional flexion assistance, (2) unidirectional extension assistance, and (3) bidirectional flexion and extension assistance. Our results show that the bidirectional assistance is the most effective in reducing the COT of walking (22.7% reduction) followed by flexion (19.2%) and extension (11.7%). The flexion assistance resulted in more COT saving than the output of its net work by 35.9%, which indicates that the negative work done (42.2% of its positive counterpart) also played an important role in reducing the COT. The bidirectional assistance also reduced the activations of the hip extensors to a great extent and shifted the activation pattern of the hip flexor (ilipsoas). These results can provide valuable information for optimal hip actuation (timing and profiles) and help exoskeleton designers make informed decisions.","PeriodicalId":23602,"journal":{"name":"Volume 2: 41st Computers and Information in Engineering Conference (CIE)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2021-08-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"73331749","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Obtaining and analyzing customer and product information from various sources has become a top priority for major competitive companies who are striving to keep up with the digital and technological progress. Therefore, the need for creating a crowdsourcing platform to collect ideas from different stakeholders has become a major component of a company’s digital transformation strategy. However, these platforms suffer from problems that are related to the voluminous and vast amount of data. Different large sets of data are being spurred in these platforms as time goes by that render them unbeneficial. The aim of this paper is to propose a solution on how to discover the most promising ideas to match them to the strategic decisions of a business regarding resource allocation and product development (PD) roadmap. The paper introduces a 2-stage filtering process that includes a prediction model using a Random Forest Classifier that predicts ideas most likely to be implemented and a resource allocation optimization model based on Integer Linear Programming that produces an optimal release plan for the predicted ideas. The model was tested using real data on an idea crowdsourcing platform that remains unnamed in the paper due to confidentiality. Our prediction model has proved to be 92% accurate in predicting promising ideas and our release planning optimization problem results were found out to be 85% accurate in producing an optimal release plan for ideas.
{"title":"Optimal Release Planning Using Machine Learning and Linear Integer Programming for Ideas in a Crowdsourcing Platform","authors":"Nour J. Absi-Halabi, A. Yassine","doi":"10.1115/detc2021-68177","DOIUrl":"https://doi.org/10.1115/detc2021-68177","url":null,"abstract":"\u0000 Obtaining and analyzing customer and product information from various sources has become a top priority for major competitive companies who are striving to keep up with the digital and technological progress. Therefore, the need for creating a crowdsourcing platform to collect ideas from different stakeholders has become a major component of a company’s digital transformation strategy. However, these platforms suffer from problems that are related to the voluminous and vast amount of data. Different large sets of data are being spurred in these platforms as time goes by that render them unbeneficial.\u0000 The aim of this paper is to propose a solution on how to discover the most promising ideas to match them to the strategic decisions of a business regarding resource allocation and product development (PD) roadmap. The paper introduces a 2-stage filtering process that includes a prediction model using a Random Forest Classifier that predicts ideas most likely to be implemented and a resource allocation optimization model based on Integer Linear Programming that produces an optimal release plan for the predicted ideas. The model was tested using real data on an idea crowdsourcing platform that remains unnamed in the paper due to confidentiality. Our prediction model has proved to be 92% accurate in predicting promising ideas and our release planning optimization problem results were found out to be 85% accurate in producing an optimal release plan for ideas.","PeriodicalId":23602,"journal":{"name":"Volume 2: 41st Computers and Information in Engineering Conference (CIE)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2021-08-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"88339602","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
This paper presents a decentralized approach based on a simple set of rules to carry out multi-robot cooperative 3D printing. Cooperative 3D printing is a novel approach to 3D printing that uses multiple mobile 3D printing robots to print a large part by dividing and assigning the part to multiple robots in parallel using the concept of chunk-based printing. The results obtained using the decentralized approach are then compared with those obtained from the centralized approach. Two case studies were performed to evaluate the performance of both approaches using makespan as the evaluation criterion. The first case is a small-scale problem with four printing robots and 20 chunks, whereas the second case study is a large-scale problem with ten printing robots and 200 chunks. The result shows that the centralized approach provides a better solution compared to the decentralized approach in both cases in terms of makespan. However, the gap between the solutions seems to shrink with the scale of the problem. While further study is required to verify this conclusion, the decrease in this gap indicates that the decentralized approach might compare favorably over the centralized approach for a large-scale problem in manufacturing using multiple mobile 3D printing robots. Additionally, the runtime for the large-scale problem (Case II) increases by 27-fold compared to the small-scale problem (Case I) for the centralized approach, whereas it only increased by less than 2-fold for the decentralized approach.
{"title":"Enabling Multi-Robot Cooperative Additive Manufacturing: Centralized vs. Decentralized Approaches","authors":"Saivipulteja Elagandula, Laxmi Poudel, Wenchao Zhou, Zhenghui Sha","doi":"10.1115/detc2021-71343","DOIUrl":"https://doi.org/10.1115/detc2021-71343","url":null,"abstract":"\u0000 This paper presents a decentralized approach based on a simple set of rules to carry out multi-robot cooperative 3D printing. Cooperative 3D printing is a novel approach to 3D printing that uses multiple mobile 3D printing robots to print a large part by dividing and assigning the part to multiple robots in parallel using the concept of chunk-based printing. The results obtained using the decentralized approach are then compared with those obtained from the centralized approach. Two case studies were performed to evaluate the performance of both approaches using makespan as the evaluation criterion. The first case is a small-scale problem with four printing robots and 20 chunks, whereas the second case study is a large-scale problem with ten printing robots and 200 chunks. The result shows that the centralized approach provides a better solution compared to the decentralized approach in both cases in terms of makespan. However, the gap between the solutions seems to shrink with the scale of the problem. While further study is required to verify this conclusion, the decrease in this gap indicates that the decentralized approach might compare favorably over the centralized approach for a large-scale problem in manufacturing using multiple mobile 3D printing robots. Additionally, the runtime for the large-scale problem (Case II) increases by 27-fold compared to the small-scale problem (Case I) for the centralized approach, whereas it only increased by less than 2-fold for the decentralized approach.","PeriodicalId":23602,"journal":{"name":"Volume 2: 41st Computers and Information in Engineering Conference (CIE)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2021-08-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"86754150","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
In the trend of digital servitization, manufacturing companies have been transforming their business paradigms to Smart product-service systems (Smart PSS) by integrating products and associated services as bundles. To support the knowledge-intensive process of Smart PSS development, massive domain knowledge should be well-organized and reused. However, due to the existence of non-binary relations caused by product-service bundles (PSB) and context-awareness concerns in the Smart PSS development activities, conventional graph-based approaches for knowledge representation may lose essential information in transforming non-binary relations into binary ones, and hence cause incorrect results in the subsequent knowledge queries. To mitigate this problem, a hypergraph-based knowledge representation model for Smart PSS was proposed, which represents the non-binary relations among multiple entities with hyperedges. Technically, the knowledge source and the typical hyperedge schema in Smart PSS development are identified in this paper. A detailed case study in the scenarios of 3D printing troubleshooting and PSB recommendation was conducted to showcase the proposed hypergraph-based knowledge representation model and demonstrate its validity. The results show that the hypergraph-based knowledge model significantly relieves the sparsity in the ordinary KG by adding multiple hyperedges. It is anticipated that the proposed hypergraph knowledge representation model can serve as a fundamental study for further knowledge reasoning activities.
{"title":"A Hypergraph-Based Knowledge Representation Model for Smart Product-Service System Development","authors":"Wang Zuoxu, Li Xinyu, Chen Chun-hsien, Zheng Pai","doi":"10.1115/detc2021-66732","DOIUrl":"https://doi.org/10.1115/detc2021-66732","url":null,"abstract":"\u0000 In the trend of digital servitization, manufacturing companies have been transforming their business paradigms to Smart product-service systems (Smart PSS) by integrating products and associated services as bundles. To support the knowledge-intensive process of Smart PSS development, massive domain knowledge should be well-organized and reused. However, due to the existence of non-binary relations caused by product-service bundles (PSB) and context-awareness concerns in the Smart PSS development activities, conventional graph-based approaches for knowledge representation may lose essential information in transforming non-binary relations into binary ones, and hence cause incorrect results in the subsequent knowledge queries. To mitigate this problem, a hypergraph-based knowledge representation model for Smart PSS was proposed, which represents the non-binary relations among multiple entities with hyperedges. Technically, the knowledge source and the typical hyperedge schema in Smart PSS development are identified in this paper. A detailed case study in the scenarios of 3D printing troubleshooting and PSB recommendation was conducted to showcase the proposed hypergraph-based knowledge representation model and demonstrate its validity. The results show that the hypergraph-based knowledge model significantly relieves the sparsity in the ordinary KG by adding multiple hyperedges. It is anticipated that the proposed hypergraph knowledge representation model can serve as a fundamental study for further knowledge reasoning activities.","PeriodicalId":23602,"journal":{"name":"Volume 2: 41st Computers and Information in Engineering Conference (CIE)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2021-08-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"76092640","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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