Multi-stage manufacturing systems require the highest possible level of availability. Due to the large batch size required for proper manufacturing, it is necessary to certify failure-free manufacturing time. Specific multi-stage machines must be characterized to calculate availability. Furthermore, preventive maintenance has been studied in several cases, thus avoiding real non-production costs due to component failures. OEE and TPM standards allow to study this problem at single-stage machines. This article presents two Novel methods for decision-making and studying the effect of unexpected failures in multi-stage machines on availability optimization and penalty costs. The first explores the real penalty cost, and the second, the impact on availability. Both methods require prior characterization of the multi-stage machine and time-dependent condition adjustment of all components. A real-life case is presented to test both methods. The first allows for a more in-depth risk analysis of specific components and enables decision-making before manufacturing systems are designed by leveraging the Internet of Things and secure remote virtual access to multi-stage manufacturing systems. In the second case, the result in terms of availability appears to be lower, but the economic improvement significantly influences the end user's decision-making. The study link to OEE standards to fix a point for further researches. Keywords: Decision Making, Penalty cost, Maintenance, Availability, Multistage Machine.

In today’s society, technology dominates most areas of human life. In particular, video games play an important role and manufacturing companies do not stop innovating to present their interactivity and playability through the hardware they introduce in the market. To be competitive in this sector it is necessary to innovate from the early stages of design to obtain products that are totally innovative in their form and interactivity but that do not cause difficulties in the subsequent manufacturing phase. By applying emotional design methodologies we will be able to establish requirements and design specifications necessary to present innovative controls to the market and facilitate the subsequent manufacturing processes. This method will be applied considering the haptic part of the controller, mainly the enveloping part, to define its characteristics, from the manufacturing point of view, to obtain an innovative product that connects with the emotions and sensations of the end user, including new functionalities in the market. To design the external part of the controller through the proposed methodology for the design of the external surfaces, also for the grips, ergonomics will be taken into account.

The design of walking-assistance exosuits is becoming increasingly popular among those who aim at developing a light, affordable and wearable system. They are indeed an alternative to traditional exoskeletons, which tend to be bulkier and more expensive. The main advantages of exosuits, as opposed to exoskeletons, are their lower weight and price, as well as their increased wearability and kinematic compatibility with the user. Thus, it is key to optimize their design and, particularly, the number of actuators and the actuation scheme. One of the current, common ways to achieve better designs, is to conduct a Principal Component Analysis (PCA) on some of the involved variables to reduce their dimensionality and thus, simplify the actuation system. The goal of this paper is to analyze the different variables upon which PCA can be conducted and propose the resulting actuation schemes, comparing the results and determining the best design approach for the design of a synergy-based, gait-assistance exosuit. The study focuses on both postural and dynamic synergies to optimize their design. Here, both synergy types are reviewed from a design perspective, yielding different design criteria following a PCA-based study, each with their own set of advantages and disadvantages. Thus, the design of cable-driven exosuits is optimized via analysis of gait parameters related with its actuation, such as joint torque or cable extensions. Kinematics or postural synergies lead to a higher cumulative variance of the first principal component and the transmission system is simpler than the ones obtained through dynamic synergies.

The industrial manufacturing systems are increasing in complexity to market changes. One of the best challenges of this complex systems is reach the schedule production baches without unexpected failures, looking for the zero defects. The presence of Multistage Machines (MSM) at industrial manufacturing systems allow to produce big batches in very short times. Nevertheless, these types of machines normally are manufactured as an ad hoc machine and have not maintenance strategies tested for preventive or predictive actions. Also, if a component of this machine fails, the entire machine fails, causing the loss of the production batch. Recent publications have developed local preventive and predictive maintenance strategies for industrial multistage machines, as an individual machines with local work conditions in different places. Nevertheless, the accumulated knowledge of a MSM cannot be used as relevant information to improve maintenance actions in other MSM. This research develops and proposes a network system, called Master Maintenance Management (MMM) to establish a continuous connection with all MSM, working as a datalogger who collects all relevant information for all MSM and suggest maintenance warning predictive and preventive warnings for machines and use them for preventive actions in the rest of each MSM working at the same conditions. So, the capability of one machine for take a local predictive action is performed by the MMM to take a preventive action in the other machines connected to the same network. This approach has been developed with thermoforming multistage machines, who have local preventive maintenance strategy based on individual maintenance times and predictive maintenance strategy based on some distributed sensors in the machine and a behaviour algorithm, called Digital Behaviour Twin (DBT). The most relevant benefits of this approach are the limitation of unexpected failures in the connected machines by using accumulated information of other MSM, the change of the predictive actions to preventive actions, and the machine perform by design changes suggested with all the database collected.

The study of industrial multistage component's reliability, availability and efficiency poses a constant challenge for the manufacturing industry. Components that suffer wear and tear must be replaced according to the times recommended by the manufacturers and users of the machines. This paper studies the influence of the individual maintenance values of Main Time To Repair (MTTR), Time To Provisioning (TTPR) and Time Lost Production (TLP) of each component, including the type of component and operation conditions as variables that can influence deciding on the best preventive maintenance strategy for each component. The comparison between different preventive maintenance strategies, Preventive Programming Maintenance (PPM) and Improve Preventive Programming Maintenance (IPPM) provide very interesting efficiency and availability results in the components. A case study is evaluated using PPM and IPPM strategies checking the improvement in availability and efficiency of the components. However, the improvement of stock cost of components by adopting IPPM strategy supposes the search of another more optimal solution. This paper concludes with the creation of a multidimensional matrix, for that purpose, to select the best preventive maintenance strategy (PPM, IPPM or interval between PPM and IPPM) for each component of the multistage machine based on its operating conditions, type of component and individual maintenance times. The authors consider this matrix can be used by other industrial manufacturing multistage machines to decide on the best maintenance strategy for their components.

Making the correct maintenance strategy decision for industrial multistage machines (MSTM) is a constant challenge for industrial manufacturers. Preventive maintenance strategies are the most popular and provide interesting results but cannot prevent unexpected failures and consequences, such as time lost production (TLP). In these cases, a predictive maintenance strategy should be used to maintain the appropriate level of operation time. This research aims to present a model to identify the component that failed before its mean time to failure (MTTF) and, depending on whether the cause of the failure is known, propose the use of a predictive maintenance strategy and further decision-making to ensure the highest possible value from operating time. Also, it is necessary to check the reliable value of MTTF before taking certain decisions. For this research, a real case study of a MSTM was characterized component by component, setting the individual maintenance times. The initial maintenance strategy used for all the components is the preventive programming maintenance (PPM). If a component presents an unexpected failure, a method is proposed to decide whether the maintenance strategy should be changed, adding a predictive maintenance strategy to monitor said component. The research also provides a trust level to evaluate the reliable value of MTTF of each component. The authors consider this approach very useful for machine manufacturers and end users.

The study of reliability, availability and control of industrial manufacturing machines is a constant challenge in the industrial environment. This paper compares the results offered by several maintenance strategies for multi-stage industrial manufacturing machines by analysing a real case of a multi-stage thermoforming machine. Specifically, two strategies based on preventive maintenance, Preventive Programming Maintenance (PPM) and Improve Preventive Programming Maintenance (IPPM) are compared with two new strategies based on predictive maintenance, namely Algorithm Life Optimisation Programming (ALOP) and Digital Behaviour Twin (DBT). The condition of machine components can be assessed with the latter two proposals (ALOP and DBT) using sensors and algorithms, thus providing a warning value for early decision-making before unexpected faults occur. The study shows that the ALOP and DBT models detect unexpected failures early enough, while the PPM and IPPM strategies warn of scheduled component replacement at the end of their life cycle. The ALOP and DBT strategies algorithms can also be valid for managing the maintenance of other multi-stage industrial manufacturing machines. The authors consider that the combination of preventive and predictive maintenance strategies may be an ideal approach because operating conditions affect the mechanical, electrical, electronic and pneumatic components of multi-stage industrial manufacturing machines differently.

The agri-food industry has been greatly enhanced in recent years with the introduction of process control and the automation [1] of certain links in the production chain. The seasons of the year in which these machines must be operational and show robust and reliable operation, have short durations (2 to 4 months) and are therefore greatly affected by unexpected failures that cause stops on the production lines. This paper attempts to expose a comparative advantages that can be obtained in terms of availability and efficiency in the thermoforming process. With the introduction of Industry 4.0 [2, 4] and the S2 model [5] and actuator control and early action, it is possible to optimize availability and efficiency ratios on thermoformer machines. Results show that it’s possible to reduce unexpected failures by means of this optimization tools. Two improvement strategies are outlined. Maintenance Management improvement model improves response to failures but does not optimize the useful life of the components. Algorithm life optimization based on S2 model optimizes service life and improves response to failure.

In this work, the recent advances for rapid prototyping in the orthoprosthetic industry are presented. Specifically, the manufacturing process of orthoprosthetic aids are analysed, as thier use is widely extended in orthopedic surgery. These devices are devoted to either correct posture or movement (orthosis) or to substitute a body segment (prosthesis) while maintaining functionality. The manufacturing process is traditionally mainly hand-crafted: The subject’s morphology is taken by means of plaster molds, and the manufacture is performed individually, by adjusting the prototype over the subject. This industry has incorporated computer aided design (CAD), computed aided engineering (CAE) and computed aided manufacturing (CAM) tools; however, the true revolution is the result of the application of rapid prototyping technologies (RPT). Techniques such as fused deposition modelling (FDM), selective laser sintering (SLS), laminated object manufacturing (LOM), and 3D printing (3DP) are some examples of the available methodologies in the manufacturing industry that, step by step, are being included in the rehabilitation engineering market—an engineering field with growth and prospects in the coming years. In this work we analyse different methodologies for additive manufacturing along with the principal methods for collecting 3D body shapes and their application in the manufacturing of functional devices for rehabilitation purposes such as splints, ankle-foot orthoses, or arm prostheses.

Laparoscopic surgery techniques are customarily used in non-invasive procedures. That said traditional surgical instruments and devices used by surgeons suffer from certain ergonomic deficiencies that may lead to physical complaints in upper limbs and back and general discomfort that may, in turn, affect the surgeon's skills during surgery. A novel design of the laparoscopic gripper handle is presented and compared with one of the most used instruments in this field in an attempt to overcome this problem. The assessment of the ergonomic feature of the novel design was performed by using time-frequency analysis of the surface electromyography (sEMG) signal during dynamic activities. Singular Spectrum Analysis (SSA) was used to decompose the sEMG signal and extract the median frequency of each muscle to assess muscle fatigue. The results reveal that using the proposed ergonomic grip reduces the mean values of the muscle activity during each of the proposed tasks. The novel design also improves the ease of use in laparoscopic surgery as it minimises high-pressure contact areas, reduces large amplitude movements and promotes a neutral position of the hand, wrist and forearm. Furthermore, the SSA method for time-frequency analysis provides a powerful tool to analyse a prescribed activity in ergonomic terms. The proposed methodology to assess muscle activity during surgery activities may be useful in the selection of surgical instruments when programming extended procedures, as it provides an additional selection criterion based on the surgeon's biomechanics and the proposed activity.

The objective of this work was to design and build a fully mechanical knee orthosis. A knee orthosis should both allow control of the angle of flexion of the knee during the stance phase of the gait cycle and leave the joint free during the swing phase. Knee orthoses are normally used to assist the walking of people suffering from muscle weaknesses or gait pathologies in order to avoid excessive knee flexion during the stance phase. The design of the orthosis proposed in the present work is characterized by allowing the knee to be locked at any angle of flexion during the stance phase, and because the orthosis can be unlocked to allow the joint to be released in the swing phase without the action of any external agent, i.e., without requiring external electrical or electronic systems for the control and performance of the orthosis. These characteristics mean that the design can be adapted to the gait of any user. The proposed design consists of a set of three rods, one attached to the user's thigh, another to the calf, and the other to the foot, connected to each other by a self-locking planetary gear train (PGT).

Surface roughness is a popular index used for machined products quality and is usually used as a technical requirement for mechanical products. However, the mechanism of surface roughness formation depends on various uncontrollable factors, hence the need for quantification and measurement of surface roughness to assure high product performance in industrial applications. This paper presents a study on the use of the technique named Singular Spectrum Analysis (SSA) in the characterisation of surface roughness measurements. The paper starts by explaining the mathematical bases of this technique and then, analyses this filtering technique behaviour with examples. The most important parameter that must be chosen to apply this filter in surface roughness measurement is the window length. SSA has been applied on a series of machined surfaces, and similar results to those of the ISO standard have been obtained. The BAC (Bearing Area Curve – first proposed by Abbott and Firestone) curves, spectral content and coordinate profile obtained are also similar. Based on the results, it can be concluded that the SSA technique is an interesting alternative for surface roughness analysis, even though the ISO standard does not currently cover its implementation.

When designing any rehabilitation, sportswear or exoskeleton device the mechanical behaviour of the body segment must be known, specifically the skin, because an excessive tissue strain may lead to ulceration and bedsores. To date, it is not known if the kinematic variability between subjects have an effect on the skin strain field, and therefore, in the design and manufacturing of rehabilitation products, such as orthoses. Several studies have analysed the skin deformation during human motion, nevertheless, the comparison between the skin strain field in different subjects during normal or pathological gait has not been reported yet. This work presents a comparison of skin strain analysis for different gait patterns to study the differences between people and, specifically, if it is possible to standardize the orthotic design between subjects with the same gait disorder. Moreover, the areas with relatively minimum strain during the ankle-foot motion are compared to improve the design of structural parts of rehabilitation devices. In this case, a validated 3D digital image correlation system has been used for this purpose combined with strain ellipse theory. The results demonstrate variations in the skin strain field between subjects with the same pathology and similarities between subjects with normal gait. However, more studies and experiments are necessaries to validate this hypothesis and also to test it between different gait pathologies.

Heating, ventilating and air conditioning systems in hospital operating theatres consume high amounts of energy, operate for long periods of time and provide high performance. For this reason, it is necessary to study their energy consumption and determine sustainable solutions that optimize their operation and improve their performance. In this paper, annual thermal energy consumption of a conventional operating theatre is evaluated. Potential energy savings is evaluated by maintaining an adequate indoor environmental quality for these rooms. In addition, how to minimize energy consumption depending on the air renewal flow rate used and installing a sensible heat recovery system was studied. Results show that energy demand of an operating room is reduced by 24.1% by recirculating 25% of air flow extracted from the room. Energy cost decreases 44.31% by increasing the recirculated air flow rate to 50% of the air flow extracted from the room.

Tools to encourage active participation and interaction between students and teachers through personal response systems have been incorporated into the educational arena in recent years. In this sense, this paper shows a teaching methodology used at the University of Extremadura to assess students' competencies in real time in the area of Manufacturing Engineering, using a teaching tool called Socrative. The methodology was applied in the technical subjects and involved students from the School of Industrial Engineering (Badajoz) and the University Centre of Merida (UCM). The primary objective was to assess the specific competencies in the area of Manufacturing Engineering and ascertain the most relevant cross-sectional competencies students need to acquire in these subjects, which must also be assessed. The results reveal that students improve their skills and abilities, as well as their interest in the essential contents of the curriculum and show great satisfaction with the introduction of this type of activity as a complement to the classes. Finally, it should be pointed out that these methodologies, although they have resulted in improved results in the teaching-learning process in the subjects related with manufacturing engineering, require a considerable effort of coordination on the part of teachers.

A wheelchair user faces many difficulties in their everyday attempts to use ramps, especially those of some length. The present work describes the design and build of a propulsion system for manual wheelchairs for use in ascending or descending long ramps. The design is characterized by a self-locking mechanism that activates automatically to brake the chair when the user stops pushing. The system consists of a planetary transmission with a self-locking capacity coupled to a push rim with which the user moves the system. Different transmission ratios are proposed, adapted to the slope and to the user's physical capacity (measured as the power the user can apply over ample time periods). The design is shown to be viable in terms of resistance, and approximate dimensions are established for the height and width of the propulsion system. Also, a prototype was built in order to test the self-locking system on ramps.

In the new context of the European Higher Education Framework (Bologna Process), the lecturers must cope with the educational achievement assessment and with an appropriate control of the educational process. In this paper, we present the methodology used in the University of Extremadura to evaluate the educational competences in the real time by means of Socrative (by Mastery Connect) launched in smartphones, tablets, laptops, etc. This study has been carried out with the students of two Faculties: the School of Industrial Engineering and the University Centre of Merida, in the framework of an educational innovation project focused on several technical subjects for the mechanical engineering and industrial design degrees. The result shows that the students have improved their competences and their skills, and also the interest in the core syllabus contents, and a great satisfaction with the introduction of this type of activities as a complement to the lectures. Finally, they value this educational experience by means of a surveying, obtaining marks between 83%-85% of the students that consider it as a "positive'' or "very positive'' experience. The conclusions of this study show that with the use of this tool (Socrative), the students are more motivated and interested in the content of the subjects, with an improvement of their collaborative attitude in the class. It leads to obtain an outstanding performance, with a failure rate that in our case, has been reduced by a 20% from "classical'' methodology. In contrast, the implementation of this new technological tool demands a notable effort from lecturers' coordination, besides a supplementary work.

A study was carried out with 135 surgeons to obtain a surgical laparoscopic grasper handle design that adapts to the size of each surgeon’s hand, in a functionally appropriate way, and has the sufficient ergonomics to avoid generating the problems detected nowadays. The main conclusion of the work is the practical 3D parametric design obtained for a laparoscopic surgical graspers handle that is scalable to fit each particular surgeon's hand size. In addition, it has been possible to determine that the anthropometric measure of the surgeon's hand defined as Palm Length Measured (PLM) allows the design of the 3D parametric model of the surgical handle to be conveniently scaled. The results show that both additive manufacturing and the application of ergonomics criterion provide an efficient method for the custom design and manufacture of this type of specialised tool, with potential application in other sectors.

The development of dynamic orthoses is a fast-growing field of research and has resulted in many different devices, where all of them try to solve or correct some motion pathology. As these devices are held on the human skin, is behaviour must be a source of inspiration for the safety design of wearable devices Pt Furthermore, to design a comfortable orthosis the joint motion must be considered. Based on this, the approach of this work for the design of rehabilitation orthotics is to analyse the skin strain field during a prescribed rehabilitation motion. Then, based on anatomical lines with minimum deformation, also called, Lines of non-extension (LoNES) it is possible to design the structural parts of the orthosis. This LoNEs can be obtained from the recorded motion by Digital Image Correlation and different optimization criteria. The structural parts of the orthotic can be designed over these lines, and consequently these parts must be considered as slender structures. In this work, the complete process to obtain a functional orthotic device is presented. The design of the slender contours of the orthotic and the optimization (material selection, thicknes, etc.) based on finite element analysis is also described. Different prototypes are analysed to determine the areas with major strain. The resulting prototype is optimize the design based on this information.