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This study aims to investigate the suitability of a multi-step prototyping strategy for producing pneumatic rotary vane actuators (RVAs) for the development of lightweight robots and actuation systems.

RVAs typically have cast aluminum housings and injection-molded seals that consist of hard thermoplastic cores and soft elastomeric overmolds. Using a combination of additive manufacturing (AM), computer numerical control (CNC) machining and elastomer molding, a conventionally manufactured standard RVA was replicated. The standard housing design was modified, and polymeric replicas were obtained by selective laser sintering (SLS) or PolyJet (PJ) printing and subsequent CNC milling. Using laser-sintered molds, actuator seals were replicated by overmolding laser-sintered polyamide cores with silicone (SIL) and polyurethane (PU) elastomers. The replica RVAs were subjected to a series of leakage, friction and durability experiments.

The AM-based prototyping strategy described is suitable for producing functional and reliable RVAs for research and product development. In a representative durability experiment, the RVAs in this study endured between 40,000 and 1,000,000 load cycles. Frictional torques were around 0.5 Nm, which is 10% of the theoretical torque at 6 bar and comparable to that of the standard RVA. Models and parameters are provided for describing the velocity-dependent frictional torque. Leakage experiments at 10,000 load cycles and 6 bar differential pressure showed that PJ housings exhibit lower leakage values (6.8 L/min) than laser-sintered housings (15.2 L/min), and PU seals exhibit lower values (8.0 l/min) than SIL seals (14.0 L/min). Combining PU seals with PJ housings led to an initial leakage of 0.4 L/min, which increased to only 1.2 L/min after 10,000 load cycles. Overall, the PU material used was more difficult to process but also more abrasion- and tear-resistant than the SIL elastomer.

More work is needed to understand individual cause–effect relationships between specific design features and system behavior.

To date, pneumatic RVAs have been manufactured by large-scale production technologies. The absence of suitable prototyping strategies has limited the available range to fixed sizes and has thus complicated the use of RVAs in research and product development. This paper proves that functional pneumatic RVAs can be produced by using more accessible manufacturing technologies and provides the tools for prototyping of application-specific RVAs.

The emerging industrial revolution referred to as Industry 5.0 is focusing on leveraging human creativity with intelligent and autonomous systems to derive user-friendly work environment for the businesses. Industry 5.0 stresses on people centric work ecosystem, zero accident policy and the well-being of labour within the production processes. This approach of Industry 5.0 to obtain human-centric safety solutions through the deployment of digital technologies deduces workplace accidents and costs leading to the development of Safety 4.0. This chapter aims to investigate the opportunities and challenges of Safety 4.0 and its enabling technologies aspiring towards the greater impact on safety management. Further, we have proposed a framework for the role of human centric digital transformations concerning safety in the manufacturing industry propelling Safety 4.0. Concluding, we discuss the implications for managers and practitioners. We found that Safety 4.0 will strengthen industrial safety, and instead of reacting to accidents, the concept evolved towards a preventive and proactive approach for a healthy industrial ecosystem.

The purpose of this paper is to develop a control strategy for human–robot collaborative manipulation tasks that can deal with proximity signals from 373 interconnected cells of an artificial skin.

The robot and the operator accomplish an industrial task while interacting in a shared workspace. The robot controller detects and avoids collisions based on the information from the artificial skin. Conflicting constraints can be handled by prioritizing between hard and soft constraints or by weighing the different constraints.

Weak soft constraints (low weight) are specified to command the robot to move along a nominal path with constant velocity. Stronger soft constraints (higher weight) prevent collisions by means of either moving the end effector backward along the path or circumventing an obstacle. The proposed approach is validated experimentally.

As a first contribution, this paper proposes a discrete optimization algorithm activates an a priori selected maximum number of cells. The algorithm selects the appropriate distribution based on the amplitude of each signal and the spatial distribution of the proximity measurements. A second contribution is the specification of a human–robot collaborative application as an optimization problem using eTaSL (expression graph-based task specification language), which provides reactive control.

Camel as a livestock plays an important role in desert ecosystem and its milk has potential contribution in human nutrition in the hot and arid regions of the world. This milk contains all the essential nutrients as found in other milk. Fresh and fermented camel milk has been used in different regions in the world including India, Russia and Sudan for human consumption as well as for treatment of a series of diseases such as dropsy, jaundice, tuberculosis, asthma and leishmaniasis or kala-azar. The present paper aims to explore the possibility of camel milk as an alternative milk for human consumption.

Recently, camel milk and its components were also reported to have other potential therapeutic properties, such as anti-carcinogenic, anti-diabetic, anti-hypertensive and renoprotective potential; and for autism, and has been recommended to be consumed by children who are allergic to bovine milk.

It has also been reported to alleviate oxidative stress and lipid peroxidation in rats. Camel milk differs from bovine milk in composition. It contains low total solids and fat; however, proteins and lactose are in equal amount but of higher quality than cow milk. Because of the high percentage of β-casein, low percentage of α-casein, deficiency of β-lactoglobulin and similarity of the immunoglobulins, it become safer for persons who are allergic to bovine milk. It contains protective proteins in higher amount which contributes to its functionality. The fermentation and enzymatic hydrolysis of camel protein produce different types of bioactive peptides which exerts different activity in in vitro and in vivo conditions.

Because of its unique quality and functionality, this milk has potential application in management of different diseases and application in food industries.

The purpose of this paper is a description of DITCI, its drop loads and sensors, the impact tools, the robot dynamic impact safety artifacts, data analysis, and modeling of test results. The dynamic impact testing and calibration instrument (DITCI) is a simple instrument with a significant data collection and analysis capability that is used for the testing and calibration of biosimulant human tissue artifacts. These artifacts may be used to measure the severity of injuries caused in the case of a robot impact with a human.

In this paper, we describe the DITCI adjustable impact and flexible foundation mechanism, which allows the selection of a variety of impact force levels and foundation stiffness. The instrument can accommodate arrays of a variety of sensors and impact tools, simulating both real manufacturing tools and the testing requirements of standards setting organizations.

A computer data acquisition system may collect a variety of impact motion, force and torque data, which are used to develop a variety of mathematical model representations of the artifacts. Finally, we describe the fabrication and testing of human abdomen soft tissue artifacts with embedded markers, used to display the severity of impact injury tissue deformation.

DITCI and the use of biosimulant human tissue artifacts will permit a better understanding of the severity of injury, which will be caused in the case of a robot impact with a human, without the use of expensive cadaver parts. The limitations are set by the ability to build artifacts with material properties similar to those of various parts of the human body.

This technology will be particularly useful for small manufacturing companies that cannot afford the use of expensive instrumentation and technical consultants.

Impact tests were performed at maximum impact force and average pressure levels that are below, at and above the levels recommended by a proposed International Organization for Standardization standard. These test results will be used to verify whether the adopted safety standards will protect interactive robots human operators for various robot tools and control modes.

Various research groups have used human subjects to collect data on pain induced by industrial robots. Unfortunately, human safety testing is not an option for human–robot collaboration in industrial applications every time there is a change of a tool or control program, so the use of biosimulant artifacts is expected to be a good alternative.

Collaborative robotics and autonomous driving are fairly new disciplines, still with a long way to go to achieve goals, set by the research community, manufacturers and users. For technologies like collaborative robotics and autonomous driving, which focus on closing the gap between humans and machines, the physical, psychological and emotional needs of human individuals becoming increasingly important in order to ensure effective and safe human–machine interaction. The authors' goal was to conceptualize ways to combine experience from both fields and transfer artificial intelligence knowledge from one to another. By identifying transferable meta-knowledge, the authors will increase quality of artificial intelligence applications and raise safety and contextual awareness for users and environment in both fields.

First, the authors presented autonomous driving and collaborative robotics and autonomous driving and collaborative robotics' connection to artificial intelligence. The authors continued with advantages and challenges of both fields and identified potential topics for transferrable practices. Topics were divided into three time slots according to expected research timeline.

The identified research opportunities seem manageable in the presented timeline. The authors' expectation was that autonomous driving and collaborative robotics will start moving closer in the following years and even merging in some areas like driverless and humanless transport and logistics.

The authors' findings confirm the latest trends in autonomous driving and collaborative robotics and expand them into new research and collaboration opportunities for the next few years. The authors' research proposal focuses on those that should have the most positive impact to safety, complement, optimize and evolve human capabilities and increase productivity in line with social expectations. Transferring meta-knowledge between fields will increase progress and, in some cases, cut some shortcuts in achieving the aforementioned goals.

This study aims to produce a new type of healthy functional kefir by adding olive (Olea europaea) leaf extract and to determine its potential effect on the quality (physicochemical, sensory, phenolic contents and antioxidant properties) of kefir samples during storage at 4°C for 21 days.

For this purpose, four kefir samples were produced by using olive leaf extract in different amounts (A: 0% (control), B: 0.1%, C: 0.15% and D: 0.35%). The physicochemical, sensory, phenolic contents and antioxidant properties of kefir samples were investigated during Days 1, 7, 14 and 21 of storage. The study was conducted to optimize the olive leaf extract addition level to obtain better-quality kefir functional food.

From the results, it was determined that the addition of olive leaf extract affected the entire chemical components of the kefir samples (p < 0.05). It was found that the pH value decreased during storage. By contrast, it was observed that titration acidity values increased. The kefir sample with 0.35% olive leaf extract (D) had the highest total phenolic and antioxidant activity content (1,292.75 mg GAE/L and 10.20 mM TE, respectively) among the samples (p < 0.05). In the sensory analyses, the kefir sample with the highest score – in terms of sensory attributes – was the kefir sample containing 0.15% olive leaf extract (C).

Thus, it was concluded that kefir with added olive leaf extract could serve as a functional kefir of benefit to human health. When we looked at the enrichment studies on kefir as a functional product, no study has been found on the use of olive (Olea europaea) leaf extract, especially with kefir. In this sense, it is thought that the study will contribute to published literature.

The purpose of this paper is to report a survey in random-selected supermarkets in Italy in order to identify the attitudes and perceptions of consumers toward milk and in particular toward donkey milk.

The analysis was conducted through Google Forms platform of docs.google interviews with a sample of 705 consumers who were given a questionnaire to collect information about their economic status and their attitudes toward milk and special milk consumption.

The results were analyzed in order to identify the socio-economic and behavioral characteristics of homogeneous groups of consumers. They consume milk mainly because it is not expensive and it is possible to easily buy it in the supermarket. They consume special milk mainly because of food allergies or intolerances. They would like to buy special milk at large-scale retail trade outlets; they underline difficulties in finding and purchasing it. They think that the price of special milk is very high.

The results showed that those who occasionally consume special milk choose it because it is more nourishing or for health reasons; there is also a significant association between the judgment on prices of special milk and the frequency of purchase. The estimation of a generalized linear model allowed to highlight that only age and the presence of health problems/intolerances are significant predictors of special milk consumption.

In the present era of Industry 4.0, the manufacturing automation is moving toward mass production and mass customization through human–robot collaboration. The purpose of this paper is to describe various human–robot collaborative (HRC) techniques and their applicability for various manufacturing methods along with key challenges.

Numerous recent relevant research literature has been analyzed, and various human–robot interaction methods have been identified, and detailed discussions are made on one- and two-way human–robot collaboration.

The challenges in implementing human–robot collaboration for various manufacturing process and the challenges in one- and two-way collaboration between human and robot are found and discussed.

The authors have attempted to classify the HRC techniques and demonstrated the challenges in different modes.

Interaction plays a significant role in robotics and it is considered in all levels of hardware and software control design. Several models have been introduced and developed for controlling robotic interaction. This study aims to address and analyze the state-of-the-art on robotic interaction control by which it is revealed that both practical and theoretical issues have to be faced when designing a controller.

In this review, a critical analysis of the control algorithms developed for robotic interaction tasks is presented. A hierarchical classification of distributed control levels from general aspects to specific control algorithms is also illustrated. Hence, two main control paradigms are discussed together with control approaches and architectures. The challenges of each control approach are discussed and the relevant solutions are presented.

This review presents an evolvement trend of interaction control theories and technologies over time. In addition, it highlights the pros and cons of each control approaches with addressing how the flaws of one control approach were compensated by emerging another control methods.

This review provides the robotic controller designers to select the right architecture and accordingly design the appropriate control algorithm for any given interactive task and with respect to the technology implemented in robotic manipulator.