Teleoperator-Robot-Human Interaction in Manufacturing: Perspectives from Industry, Robot Manufacturers, and Researchers.

OCCUPATIONAL APPLICATIONSIndustrial robots have become an important aspect in modern industry. In the context of human-robot collaboration, enabling teleoperated robots to work in close proximity to local/onsite humans can provide new opportunities to improve human engagement in a distributed workplace. Interviews with industry stakeholders highlighted several potential benefits of such teleoperator-robot-human collaboration (tRHC), including the application of tRHC to tasks requiring both expertise and manual dexterity (e.g., maintenance and highly skilled tasks in sectors including construction, manufacturing, and healthcare), as well as opportunities to expand job accessibility for individuals with disabilities and older individuals. However, interviewees also indicated potential challenges of tRHC, particularly related to human perception (e.g., perceiving remote environments), safety, and trust. Given these challenges, and the current limited information on the practical value and implementation of tRHC, we propose several future research directions, with a focus on human factors and ergonomics, to help realize the potential benefits of tRHC.

Background The increasing prevalence of robots in industrial environments is attributed in part to advancements in collaborative robot technologies, enabling robots to work in close proximity to humans. Simultaneously, the rise of teleoperation, involving remote robot control, poses unique opportunities and challenges for human-robot collaboration (HRC) in diverse and distributed workspaces.Purpose There is not yet a comprehensive understanding of HRC in teleoperation, specifically focusing on collaborations involving the teleoperator, the robot, and the local or onsite workers in industrial settings, here referred to as teleoperator-robot-human collaboration (tRHC). We aimed to identify opportunities, challenges, and potential applications of tRHC through insights provided from industry stakeholders, thereby supporting effective future industrial implementations.Methods Thirteen stakeholders in robotics, specializing in different domains (i.e., safety, robot manufacturing, aerospace/automotive manufacturing, and supply chains), completed semi-structured interviews that focused on exploring diverse aspects relevant to tRHC. The interviews were then transcribed and thematic analysis was applied to group responses into broader categories, which were further compared across stakeholder industries.Results We identified three main categories and 13 themes from the interviews. These categories include Benefits, Concerns, and Technical Challenges. Interviewees highlighted accessibility, ergonomics, flexibility, safety, time & cost saving, and trust as benefits of tRHC. Concerns raised encompassed safety, standards, trust, and workplace optimization. Technical challenges consisted of critical issues such as communication time delays, the need for high dexterity in robot manipulators, the importance of establishing shared situational awareness among all agents, and the potential of augmented and virtual reality in providing immersive control interfaces.Conclusions Despite important challenges, tRHC could offer unique benefits, facilitating seamless collaboration among the teleoperator, teleoperated robot(s), and onsite workers across physical and geographic boundaries. To realize such benefits and address the challenges, we propose several research directions to further explore and develop tRHC capabilities.

Impact of industrial robot applications on global value chain participation of China manufacturing industry: Mediation effect based on product upgrading.

Promoting the application of industrial robot (IR) is an important module for China to build core competitiveness, and it is also the main grasp of global value chain participation (GVCP). Using China manufacturing industry panel data from 2006-2014, working from the perspective of product upgrading, this paper empirically analyzes the impact of IR applications on GVCP. The empirical results show that IR applications weaken China' incentives to participate in global value chains (GVCs); this weakening effect is reflected in both forward and backward participation in GVCs. On the one hand, the mediation effect test results indicate that the product upgrading effect brought about by IR applications can help China achieves the import substitution of intermediate inputs and uses local intermediate inputs to produce exports. These steps would reduce the backward participation in GVCs. On the other hand, the localization of manufacturing can result in China losing the opportunity to export intermediate inputs to other economies, thus reducing the forward participation of GVCs. Of course, due to sample limitations, the research conclusions of this article are only applicable to interpreting the Chinese economy.

Aggressive strategies of the COVID-19 pandemic on the apparel industry of Sri Lanka using structural equation modeling.

During the COVID-19 crisis, the apparel industry faced many challenges. Aggressive cost-cutting strategies became a top priority, and in turn, these influenced stressors and adversely affected business sustainability. This study examines the impact of aggressive strategies during the COVID-19 pandemic on business sustainability in the apparel industry of Sri Lanka. Further, it investigates whether the relationship between aggressive cost-cutting strategies and business sustainability was mediated by employee stress, considering aggressive cost reduction strategies and workplace environmental changes. This was a cross-sectional study with data collected from 384 employees in the apparel industry in Sri Lanka. Structural Equation Modelling (SEM) was applied to analyze the direct and indirect effects of aggressive cost reduction strategies and workplace environmental changes on sustainability with mediating effects of stress. Aggressive cost reduction strategies (Beta = 1.317, p = 0.000) and environmental changes (Beta = 0.251, p = 0.000) led to an increase in employee stress but did not affect business sustainability. Thus, employee stress (Beta = -0.028, p = 0.594) was not a mediator in the relationship between aggressive cost-cutting strategies and business sustainability; business sustainability was not a dependent variable. The findings proved that managing workplace stress, particularly improving stressful working environments and aggressive cost reduction strategies, can enhance employee satisfaction. Thus, managing employee stress could be beneficial for policymakers to focus on the area(s) required to retain competent employees. Moreover, aggressive strategies are unsuitable to apply during crisis to enhance business sustainability. The findings provide additional knowledge to the existing literature, enabling employees and employers to predict causes of stress and serve as a significant knowledge base for further studies.

Effect of lean manufacturing tools on sustainability: the case of Mexican maquiladoras.

The Mexican maquiladora industry is applying Lean Manufacturing Tools (LMT) in its production lines; however, few studies have investigated its relationship with sustainability (social, economic, and environmental). This paper presents a second-order structural equation model (SEM) relating 8 LMT integrated into three independent latent variables: continuous improvement (Kaizen and Gemba), supporting tools (Andon, visual management, and Poka-yoke), and machinery and equipment (total productive maintenance, overall equipment effectiveness, and Jidoka) that are related to social, economic, and environmental sustainability as dependent variables. The model is validated with information obtained from 249 companies using partial least squares. Findings show that the application of LMT in the Mexican maquiladora industry avoids the generation of waste and reprocessing. Likewise, the improvement of production processes reduces the waste emitted into the environment and reduces energy consumption. Also, when companies have environmental programs, the work environment is safe, and labor relations are improved, increasing morale and the commitment to work for the company, gaining economic and ecological benefits.

Evaluation of Starch as an Environmental-Friendly Bioresource for the Development of Wood Bioadhesives.

The environment is a very complex and fragile system in which multiple factors of different nature play an important role. Pollution, together with resource consumption, is one of the main causes of the environmental problems currently affecting the planet. In the search for alternative production processes, the use of renewable resources seeks a way to satisfy the demands of resource consumption based on the premises of lower environment impact and less damage to human health. In the wood sector, the panel manufacturing process is based on the use of formaldehyde-based resins. However, their poor moisture resistance leads to hydrolysis of amino-methylene bonds, which induces formaldehyde emissions throughout the lifetime of the wood panel. This manuscript investigates the environmental profile associated with different wood bioadhesives based on starch functionalization as a renewable alternative to formaldehyde resins. Considering that this is a process under development, the conceptual design of the full-scale process will be addressed by process modeling and the environmental profile will be assessed using life cycle assessment methodology. A comparative study with synthetic resins will provide useful information for modify their development to become real alternatives in the wood-based panel industry. The results obtained show the enormous potential of starch bioadhesives, as their environmental impact values are lower compared to those based on petrochemicals. However, certain improvements in the energy process requirements and in the chemical agents used could be developed to provide even better results.

Evaluation and spatial agglomeration analysis of the green competitiveness of China's manufacturing industry at the provincial level.

The pressures to maintain a low-carbon economy makes green competitiveness (GC) a significant issue in China. It has been found that the development of Internet and E-commerce contributes significantly to GC of regional economy, yet there are still lack of quantitative investigation on their effects, which can be used to further guide the economic development. Therefore, this study constructs a new evaluation index for the green competitiveness of the regional manufacturing industry in China by introducing Internet application indicators and E-commerce development indexes into its evaluation system. The results show Jiangxi and Gansu moved upward significantly in the GC ranking over the period. The development of the Internet and E-commerce has the most significant impact on GC of regional manufacturing. The lack of green manufacturing capabilities and green innovation drivers led to a decline in the GC ranking of Liaoning, Tianjin, Guangxi and Heilongjiang. Finally, this study uses Moran's I index to investigate the spatial agglomeration effect of the green development of the manufacturing industry at the province level. The results show an increase in the GC of China's regional manufacturing industry, and the GC of manufacturing industry shows a significant agglomeration effect. Based on the above conclusions, the proposal to promote the balanced development of the GC of the manufacturing industry is proposed.

Application of a simulation model to the prognosis of material loss in wood processing.

The article discusses the influence of a sample size on the credibility of a simulation model created for the estimation of material loss in the production of a middle layer of a wooden floorboard. The study was conducted in a production company operating in the wood processing industry. Geometric characteristics of input material were captured and used to derive statistical distributions, which were then included in the simulation model. The conducted experiments indicated that the quality of the simulation model was significantly affected by the quality and quantity of the sample, on the basis of which the stochastic model is estimated. It was shown that small sample for wood processing data was insufficient to capture process variability. On the other hand, excessive sample size (80 or more observations) for the material with high natural geometric variability, involves taking into account outliers, which may lower the overall prognostic quality of the simulation model. Based on the conducted simulation experiments, the recommended sample size which allows development of a reliable model for estimation of material loss in the analyzed manufacturing process, ranges from 40 to 60 measurements.

Recognition of industrial machine parts based on transfer learning with convolutional neural network.

As the industry gradually enters the stage of unmanned and intelligent, factories in the future need to realize intelligent monitoring and diagnosis and maintenance of parts and components. In order to achieve this goal, it is first necessary to accurately identify and classify the parts in the factory. However, the existing literature rarely studies the classification and identification of parts of the entire factory. Due to the lack of existing data samples, this paper studies the identification and classification of small samples of industrial machine parts. In order to solve this problem, this paper establishes a convolutional neural network model based on the InceptionNet-V3 pretrained model through migration learning. Through experimental design, the influence of data expansion, learning rate and optimizer algorithm on the model effectiveness is studied, and the optimal model was finally determined, and the test accuracy rate reaches 99.74%. By comparing with the accuracy of other classifiers, the experimental results prove that the convolutional neural network model based on transfer learning can effectively solve the problem of recognition and classification of industrial machine parts with small samples and the idea of transfer learning can also be further promoted.

Nanofabrication for all-soft and high-density electronic devices based on liquid metal.

Innovations in soft material synthesis and fabrication technologies have led to the development of integrated soft electronic devices. Such soft devices offer opportunities to interact with biological cells, mimicking their soft environment. However, existing fabrication technologies cannot create the submicron-scale, soft transducers needed for healthcare and medical applications involving single cells. This work presents a nanofabrication strategy to create submicron-scale, all-soft electronic devices based on eutectic gallium-indium alloy (EGaIn) using a hybrid method utilizing electron-beam lithography and soft lithography. The hybrid lithography process is applied to a biphasic structure, comprising a metallic adhesion layer coated with EGaIn, to create soft nano/microstructures embedded in elastomeric materials. Submicron-scale EGaIn thin-film patterning with feature sizes as small as 180 nm and 1 µm line spacing was achieved, resulting in the highest resolution EGaIn patterning technique to date. The resulting soft and stretchable EGaIn patterns offer a currently unrivaled combination of resolution, electrical conductivity, and electronic/wiring density.

Optimization design of a novel X-type six-high rolling mill based on maximum roll system stiffness.

The present investigation devices a novel X-type six-high (X-6h) mill. In addition, parametric models of different roll layouts such as the four-high (4-h), I-type six-high (I-6h), and X-6h mills are established. Three-dimensional (3D) finite element (FE) contact analysis for a strip rolling process is conducted when the mills are subjected to a constant vertical load of 65 kN. Through comparative analysis of von Mises stress, contact stress and elastic deformation displacement in three roll layouts, the rigidity characteristic of each is obtained, and it is found that the proposed X-6h mill has the largest roll gap stiffness. The influence of different roll diameter ratios on the roll gap stiffness of the roll system is investigated, based on which an optimization design model is built. Further, by taking into account the roll gap stiffness of the roll system as the optimization objective, the optimum diameter ratios of backup roll (BUR) to work roll (WR) of the X-6h rolling mill is achieved via the genetic algorithm (GA) optimization method, obtaining the optimum structural parameters of BUR and WR as well. The reliability of the proposed design is verified by manufacturing a prototype mill which produced magnesium alloy and aluminum alloy strips of high quality.

Research on the energy-saving control strategy of a belt conveyor with variable belt speed based on the material flow rate.

Aiming at solving the problem of high energy consumption in the rated belt speed operation of a belt conveyor system when the material flow rate is reduced, the power consumption of the frequency converter, motor, and belt conveyor is analyzed, a power consumption model of the belt conveyor system is established, the relationship between the power consumption of the belt conveyor system and belt speed is obtained, and a energy-saving control strategy of the belt conveyor with variable belt speed based on the material flow rate is put forward. The energy consumption of the belt conveyor is analyzed for a practical case. Results show that the power consumption model is accurate and the control strategy effectively reduces energy consumption. The model has high application value in coal, ports, power, mine, metallurgy, chemical, and other industries.

The role of services content for manufacturing competitiveness: A network analysis.

This paper explores the phenomenon of international servicification of manufacturing from the period 1995 to 2011. By applying empirical techniques of Social Network Analysis and graph theory, we find that the network of flows of intermediate services embodied in manufacturing exports is still slightly dense and would not correspond to a traditional centre-periphery structure. The mapping shows a numerous, highly cohesive group of countries, with China, the USA and Germany as central economies and an increasing leading role of Asian economies, which would indicate their commitment to upgrading within global value chains. We go a step further by empirically analysing the impact of the countries' centrality in the global network of intermediate services on manufacturing competitiveness. Our findings reveal that, together with the level of embodiment of intermediate services into manufacturing exports, who the providers of those services inputs are is a key determining factor for manufacturing competitiveness.

The Role of Gender, Academic Affiliation, and Subspecialty in Relation to Industry Payments to Orthopaedic Surgeons.

BACKGROUND: The Physician-Payments-Sunshine-Act (PPSA) was introduced in 2010 to provide transparency regarding physician-industry payments by making these payments publicly available. Given potential ethical implications, it is important to understand how these payments are being distributed, particularly as the women orthopaedic workforce increases. The purpose of this study was thus to determine the role of gender and academic affiliation in relation to industry payments within the orthopaedic subspecialties. METHODS: The PPSA website was used to abstract industry payments to Orthopaedic surgeons. The internet was then queried to identify each surgeon's professional listing and gender. Mann-Whitney U, Chi-square tests, and multivariable regression were used to explore the relationships. Significance was set at a value of P < 0.05. RESULTS: In total, 22,352 orthopaedic surgeons were included in the study. Payments were compared between 21,053 men and 1299 women, 2756 academic and 19,596 community surgeons, and across orthopaedic subspecialties. Women surgeons received smaller research and non-research payments than men (both, P < 0.001). There was a larger percentage of women in academics than men (15.9% vs 12.1%, P < 0.001). Subspecialties with a higher percentage of women (Foot & Ankle, Hand, and Pediatrics) were also the subspecialties with the lowest mean industry payments (all P < 0.001). Academic surgeons on average, received larger research and non-research industry payments, than community surgeons (both, P < 0.001). Multivariable linear regression demonstrated that male gender (P = 0.006, P = 0.029), adult reconstruction (both, P < 0.001) and spine (P = 0.008, P < 0.001) subspecialties, and academic rank (both, P < 0.001) were independent predictors of larger industry research and non-research payments. CONCLUSIONS: A large proportion of the US orthopaedic surgeon workforce received industry payments in 2014. Academic surgeons received larger payments than community surgeons. Despite having a larger percentage of surgeons in academia, women surgeons received lower payments than their male counterparts. Women also had a larger representation in the subspecialties with the lowest payments.

Task engagement as a mediator between the cognitive demands of sustained attention and musculoskeletal complaints: A structural equation modelling approach.

BACKGROUND: Cognitive demands in the form of sustained attention are prevalent in automated manufacturing where operators undertake monitoring tasks for prolonged periods. Sustained attention tasks are stressful and could have potential health consequences for employees including contributing to Work Related Musculoskeletal Disorders (WRMSDs). OBJECTIVE: The study investigates if lowered task engagement (low task motivation/focus) is a mediator of the relationship between sustained attention and musculoskeletal complaints. METHOD: A structural equation modelling technique was used to determine if task engagement mediates the relationship between attention demand/attention supply and self-reported musculoskeletal complaints (MSCs) in manufacturing employees (n = 235). RESULTS: Study participants were 5.16 times (OR, odds ratio) more likely to have neck complaints, 7.27 (OR) times more likely to have upper back complaints and 3.9 (OR) times more likely to report lower back complaints (OR 2.05) when attention demands were high and task engagement was low. When task engagement was introduced as a mediator between attention supply and MSCs, odds ratios decreased for neck (from 1.01 to 0.60), shoulder (from 0.95 to 0.47) (p < 0.01), upper back (from 1.01 to 0.70) (p < 0.01) and lower back (from 0.94 to 0.40)*. CONCLUSION: Task engagement was a significant mediator of the relationship between attention demand and neck, upper back and lower back musculoskeletal complaints for study participants.

Assessing the effects of lean on occupational health and safety in the Ready-Made Garment industry.

BACKGROUND: Garment manufacturers have been adopting lean manufacturing in order to increase productivity and competitiveness. However, the effects of lean on occupational health and safety (OHS) of the workers are not clear. In the literature, there is an ongoing debate about whether lean and OHS are complementary or contradictory. OBJECTIVE: The goal of this study was to contribute to the knowledge base about the relationship between lean and OHS in garment manufacturing. METHODS: The study follows an action research methodology including an intervention aimed at improving productivity and OHS in six garment manufacturers in Bangladesh. Both quantitative and qualitative methods were used for investigating the effect of lean tools on productivity and subsequently on OHS. RESULTS: We observed instances of improvements of OHS related to the application of three lean tools (VSM, 5 S, Time and Motion Study) in the factories. Furthermore, our results do not indicate negative health effect on workers' short-term muscular pain, but rather show a statistically significant improvement of workers' health. CONCLUSIONS: The results suggest that it is possible to apply lean without adverse effects for workers, if OHS risks are taken into consideration. However, possible long-term effects on workers' health need to be further investigated.

Efficient Chemo-Enzymatic Transformation of Animal Biomass Waste for Eco-Friendly Leather Production.

Enzymatically processed animal biomass derived from treated bovine hides (wet blue scraps) is herein used as building block for the synthesis of a novel biopolymer. An enzymatic hydrolysis process allows to produce water-soluble lower molecular weight proteins (Bio-A), which are then reacted with glycerol and maleic anhydride (MA) in order to obtain a new intermediate (Bio-IA). With Bio-IA in hand, co-polymerization in the presence of acrylic acid is then carried out. Hydrolysed biomass, intermediates and the final biopolymer (Bio-Ac) have been characterized by means of NMR, FTIR and GPC analysis. Bio-Ac shows good performance when used as retanning agent to produce leather. Physical and mechanical properties of the leather treated with Bio-Ac have been compared with acrylic resin retanned leather, showing similar performance. The reported protocol represents an environmental-friendly interesting alternative to traditional petrochemical based retanning agents, commonly used by the leather industry.

Prediction of formation force during single-point incremental sheet metal forming using artificial intelligence techniques.

Single-point incremental forming (SPIF) is a technology that allows incremental manufacturing of complex parts from a flat sheet using simple tools; further, this technology is flexible and economical. Measuring the forming force using this technology helps in preventing failures, determining the optimal processes, and implementing on-line control. In this paper, an experimental study using SPIF is described. This study focuses on the influence of four different process parameters, namely, step size, tool diameter, sheet thickness, and feed rate, on the maximum forming force. For an efficient force predictive model based on an adaptive neuro-fuzzy inference system (ANFIS), an artificial neural network (ANN) and a regressions model were applied. The predicted forces exhibited relatively good agreement with the experimental results. The results indicate that the performance of the ANFIS model realizes the full potential of the ANN model.

Effects of environmental regulation on the upgrading of Chinese manufacturing industry.

In recent years, China has constantly strengthened environmental regulation (ER) to force the manufacturing industry to upgrade. This study theoretically analyzes interaction mechanism of ER on the upgrading of manufacturing industry through foreign direct investment (FDI) and technological innovation (TI) and carries out empirical verification by using provincial panel data from 2000 to 2016 in China. The results demonstrate that the current ER intensity in China is unable to directly promote the upgrading of manufacturing industry, while through the interaction effects of FDI and TI do boost the upgrading of the industry. The above mechanisms are also robust even if we take the regional heterogeneity into consideration. Basic education and urbanization are favorable for the upgrading of the manufacturing industry. However, the increase in dependence on foreign trade is not conducive to upgrading manufacturing industry. Chinese government should further strengthen ER and give full play of the interaction mechanism of ER to guide the flow of foreign investment and force enterprises to carry out TI. In the meanwhile, Chinese government also needs to ensure balanced regional development, thus better promoting the upgrading of manufacturing industry.

Exploration of the adverse effects of shift work in a multicultural environment.

BACKGROUND: Given that shift work spreads across many different business sectors, studies of its adverse effects are very topical. Much research has been done on the negative impact of shift work, but many researchers have not focused on its impact in a multicultural environment. OBJECTIVE: The aim of this study was to map out how shift work is perceived by workers in two different shift regimes and two national groups. METHODS: The research was carried out on Czech manufacturing workers and Turkish airport ground personnel using a questionnaire. The impact of shift work was studied from physical, mental, social and health aspects with connection to family status and gender. For statistical evaluation, Pearson's chi-squared test of independence was used. The effect of shift work on workers' performance and scrap rate was analysed only on the sample of the manufacturing workers. RESULTS: Fifty-five Czech male workers, 49 Turkish male workers and 60 Turkish female workers participated in the survey. The dependence between sexes was confirmed for mental aspects and sleeping routines. The main difference between nationalities is in work attitude, social aspects and sleeping routines. According to the family status, the difference was confirmed in all areas except social aspects. The lowest values of productivity and the highest scrap rate were observed on night shifts and the maximum productivity and lowest scrap rates were observed on afternoon shifts. CONCLUSIONS: Some of the basic assumptions were confirmed which suggests that a multicultural environment has an influence on the perception of shift work by the nations and gende.