A portable inflatable soft wearable robot to assist the shoulder during industrial work.

Repetitive overhead tasks during factory work can cause shoulder injuries resulting in impaired health and productivity loss. Soft wearable upper extremity robots have the potential to be effective injury prevention tools with minimal restrictions using soft materials and active controls. We present the design and evaluation of a portable inflatable shoulder wearable robot for assisting industrial workers during shoulder-elevated tasks. The robot is worn like a shirt with integrated textile pneumatic actuators, inertial measurement units, and a portable actuation unit. It can provide up to 6.6 newton-meters of torque to support the shoulder and cycle assistance on and off at six times per minute. From human participant evaluations during simulated industrial tasks, the robot reduced agonist muscle activities (anterior, middle, and posterior deltoids and biceps brachii) by up to 40% with slight changes in joint angles of less than 7% range of motion while not increasing antagonistic muscle activity (latissimus dorsi) in current sample size. Comparison of controller parameters further highlighted that higher assistance magnitude and earlier assistance timing resulted in statistically significant muscle activity reductions. During a task circuit with dynamic transitions among the tasks, the kinematics-based controller of the robot showed robustness to misinflations (96% true negative rate and 91% true positive rate), indicating minimal disturbances to the user when assistance was not required. A preliminary evaluation of a pressure modulation profile also highlighted a trade-off between user perception and hardware demands. Finally, five automotive factory workers used the robot in a pilot manufacturing area and provided feedback.

Enabling commercial success of industrial biotechnology.

Commercial-scale research translation has been muted.

Efficient energy and completion time for dependent task computation offloading algorithm in industry 4.0.

Rapid technological development has revolutionized the industrial sector. Internet of Things (IoT) started to appear in many fields, such as health care and smart cities. A few years later, IoT was supported by industry, leading to what is called Industry 4.0. In this paper, a cloud-assisted fog-networking architecture is implemented in an IoT environment with a three-layer network. An efficient energy and completion time for dependent task computation offloading (ET-DTCO) algorithm is proposed, and it considers two quality-of-service (QoS) parameters: efficient energy and completion time offloading for dependent tasks in Industry 4.0. The proposed solution employs the Firefly algorithm to optimize the process of the selection-offloading computing mode and determine the optimal solution for performing tasks locally or offloaded to a fog or cloud considering the task dependency. Moreover, the proposed algorithm is compared with existing techniques. Simulation results proved that the proposed ET-DTCO algorithm outperforms other offloading algorithms in minimizing energy consumption and completion time while enhancing the overall efficiency of the system.

Control of hybrid electromagnetic bearing and elastic foil gas bearing under deep learning.

The hybrid electromagnetic and elastic foil gas bearing is explored based on the radial basis function (RBF) neural network in this study so as to improve its stabilization in work. The related principles and structure of hybrid electromagnetic and elastic foil gas bearings is introduced firstly. Then, the proportional, integral, and derivative (PID) bearing controller is introduced and improved into two controllers: IPD and CPID. The controllers and hybrid bearing system are controlled based on the RBF neural network based on deep learning. The characteristics of the hybrid bearing system are explored at the end of this study, and the control simulation research is developed based on the Simulink simulation platform. The effects of the PID, IPD, and CIPD controllers based on the RBF neural network are compared, and they are also compared based on the traditional particle swarm optimization (PSO). The results show that the thickness, spread angle, and rotation speed of the elastic foil have great impacts on the bearing system. The proposed CIPD bearing control method based on RBF neural network has the shortest response time and the best control effect. The controller parameter tuning optimization starts to converge after one generation, which is the fastest iteration. It proves that RBF neural network control based on deep learning has high feasibility in hybrid bearing system. Therefore, the results provide an important reference for the application of deep learning in rotating machinery.

Theoretical study of industrial scale closed-loop recycling counter-current chromatography separations.

Industrial separation technologies can be improved and greatly simplified by using the methods of counter-current chromatography (CCC). We have previously proposed the use of currently available solvent extraction equipment (a series of multistage columns, a cascade of centrifugal mixer-settler extractors) as large-scale CCC devices. For industrial separations, the application of closed-loop recycling counter-current chromatography (CLR CCC) methods seems to be the most promising. To improve the performance of the CLR CCC separations, semi-continuous three-stage processes (1 - continuous loading of the mixture solution over a definite time; 2 - separation of solutes in recycling closed-loop; 3 - elution of the fractions of the separated solutes with the mobile phase) can be used. The purpose of this study is to present a simple and easy to use mathematical model allowing the simulation and design of various options for implementing such separation processes and analyze the influence of its main parameters on separation efficiency.

Electromagnetic compatibility issues in hybrid wired and wireless industrial networks.

Industrial networks are currently the only communication means designed for real-time systems used in industry. Networked control systems (NCS) are still important and commonly used type of such systems operating on shop floor. As a computerized node of NCS, a programmable logic controller (PLC) is usually used. In most cases, contemporary devices of such kind are equipped with more than one network interface of various types. Typically, only one interface is activated in NCS. Sometimes, the other is used for communication between NCS and supervisory systems. Occasionally, it is additionally involved in the data transmission in the factory IT systems. In general, however, using a single network interface is a more common solution. In this paper, the mutual utilization of more than one interface is discussed in order to back up the NCS network and to manage the node-related traffic within the scope of higher level services. The question of dependability of such a system from the electromagnetic compatibility point of view is discussed. The example is provided based on Profinet via wired and wireless connection.

Saw-related injuries of the lower extremity.

INTRODUCTION: Saw-related injuries can be found in all parts of the body. Especially hand saw-related injuries are frequently encountered in the literature. The aim of the study is to present our demographic data, treatment strategy and prevention of the saw-related injuries in the lower extremity. METHODS: A retrospective analysis was conducted between 2010 and 2015 and only cases with saw-related lower extremity injuries were included in the study. These patients were analyzed according to demographic data, occupational status, procedures performed, hospitalization length of stay, return to work, and complications. RESULTS: There were 48 male and 1 female patients; their mean age was 44.06 ± 13.6 (22-77) years. The average referral time after injury was 1.51 ± 0.16 (1-7) hour. The average hospitalization length of stay was 3.76 ± 3.9 (1-22) days. Fractures were also present in 13 (26.5%) patients. Postinjury complications occurred in 18 (36.7%) patients. 4 (8.2%) of the cases did not return to the job after the injury. The average return time to the work was 2.95 ± 1.5 (1-7) months. CONCLUSION: Lower extremity saw-related injuries tend to be overwhelmingly male and most often seen distal to the extremity, especially on the medial side of the extremity. A significant number of patients did not return to the job after the injury.

Preventing slips, overruns, and cancellations: Application of system accident investigations and theory to the understanding and prevention of engineering project failures.

Organizations that develop or operate complex engineering systems are plagued by systems engineering failures like schedule overruns, budget exceedances, and project cancellations. Unfortunately, there is not much actionable guidance on why these failures happen or how to prevent them. Our approach contains two novel aspects. First, we argue that system accidents and other failures in systems engineering are manifestations of similar underlying problems. Therefore, we can leverage the literature on accident causation and the many publicly available accident investigation reports to better understand how and why failures in systems engineering occur, and to identify ways of preventing them. Second, to address the lack of concrete guidance on identifying and preventing incipient failures, we provide specific examples of each type of failure cause and of the recommendations for preventing these causes. We analyzed a set of 30 accidents and 33 project failures, spanning a range of industries, and found 23 different failure causes, most of which appear in both accidents and other project failures, suggesting that accidents and project failures do happen in similar was. We also identified 16 different recommended remedial actions. We link these causes and recommendations in a cause-recommendation network, and associate over 900 specific examples of how these causes manifested in failures, and over 600 specific examples of the associated recommended remedial actions, with each cause or recommendation.

The influence of the thermal modification of pine (Pinus sylvestris L.) wood on the creation of fine dust particles in plane milling: Fine dust creation in the plane milling of thermally modified pine wood.

OBJECTIVES: The aim of the study was to determine the effect of parameters of the thermal modification process and machining on the size distribution of dust particles of Scots pine (Pinus sylvestris L.) generated during lengthwise milling. METHOD: Unmodified wood and thermally modified wood at temperatures of 130, 160, 190, and 220°C were milled lengthwise at cutting depths of 0.5 and 2 mm. Particle size analysis was done using the sieving method. The content of the finest particles was measured using the laser diffraction method. RESULTS: The results indicate that at smaller cutting depths, more smaller particles were formed regardless of the wood modification temperature. Thermal treatment of wood does not cause significant differences in the general particle size distribution of dust. However, the content of the finest dust particles depends on the temperature of wood modification. When machined, wood thermally modified at higher temperatures results in the formation of more dust particles that may pose health risks to employees. This is particularly noticeable at a smaller cutting depth. CONCLUSION: With the increase of the temperature of the modification, the share of the finest dust particles, which are a potential threat to the health of employees, increases. To reduce dust emissions during milling of thermally modified wood, the highest possible cutting depth should be used.

A literature review on latest developments of Harmony Search and its applications to intelligent manufacturing.

The harmony search (HS) algorithm is one of the most popular meta-heuristic algorithms. The basic idea of HS was inspired by the music improvisation process in which the musicians continuously adjust the pitch of their instruments to generate wonderful harmony. Since its inception in 2001, HS has attracted the attention of many researchers from all over the world, resulting in a lot of improved variants and successful applications. Even for today, the research on improved HS variants design and innovative applications are still hot topics. This paper provides a detailed review of the basic concept of HS and a survey of its latest variants for function optimization. It also provides a survey of the innovative applications of HS in the field of intelligent manufacturing based on about 40 recently published articles. Some potential future research directions for both HS and its applications to intelligent manufacturing are also analyzed and summarized in this paper.