Application of numerical and physical modeling in designing of an X-ray luminescence separator intended for separation of ores containing luminescent minerals

The paper demonstrates the application of numerical and physical modeling to justify the design of the X-ray fluorescence separator’s material handling system. The Rocky DEM software package is a numerical modeling tool that uses the discrete element method as a mathematical apparatus. In order to increase the efficiency of the X-ray luminescence separation, the authors suggest including an additional element in the separator’s material handling system, i.e., a drum spreader that combines a handling device and an actuating mechanism. It was found out that the best loading of the drum spreader cells, in which the number of several pieces in one cell is reduced by at least 15%, is provided by a Vibrating feeder conveyor with a triangular cross-section of the profiled part of the tray compared with the tray of parabolic cross-section. In addition, the triangular section provides a double decrease in the number of pieces with rotational movement around their axes and, accordingly, an increase of at least 5% in the average velocity of the ore flow movement along the tray. The simulation of the material handling system has shown the need to reduce the height of the end partition of the drum spreader between the cells to 45 mm, which eliminates the collision of ore pieces with the partition and subsequently, their movement in the direction of rotation of the drum spreader on its outer surface, as well as the unpredictable escape of the ore pieces beyond the working space of the separator.

Genetic Algorithm-Based Trajectory Optimization for Digital Twin Robots

Mobile robots have an important role in material handling in manufacturing and can be used for a variety of automated tasks. The accuracy of the robot’s moving trajectory has become a key issue affecting its work efficiency. This paper presents a method for optimizing the trajectory of the mobile robot based on the digital twin of the robot. The digital twin of the mobile robot is created by Unity, and the trajectory of the mobile robot is trained in the virtual environment and applied to the physical space. The simulation training in the virtual environment provides schemes for the actual movement of the robot. Based on the actual movement data returned by the physical robot, the preset trajectory of the virtual robot is dynamically adjusted, which in turn enables the correction of the movement trajectory of the physical robot. The contribution of this work is the use of genetic algorithms for path planning of robots, which enables trajectory optimization of mobile robots by reducing the error in the movement trajectory of physical robots through the interaction of virtual and real data. It provides a method to map learning in the virtual domain to the physical robot.

Inferring Unobserved Events in Systems with Shared Resources and Queues

To identify the causes of performance problems or to predict process behavior, it is essential to have correct and complete event data. This is particularly important for distributed systems with shared resources, e.g., one case can block another case competing for the same machine, leading to inter-case dependencies in performance. However, due to a variety of reasons, real-life systems often record only a subset of all events taking place. To understand and analyze the behavior and performance of processes with shared resources, we aim to reconstruct bounds for timestamps of events in a case that must have happened but were not recorded by inference over events in other cases in the system. We formulate and solve the problem by systematically introducing multi-entity concepts in event logs and process models. We introduce a partial-order based model of a multi-entity event log and a corresponding compositional model for multi-entity processes. We define PQR-systems as a special class of multi-entity processes with shared resources and queues. We then study the problem of inferring from an incomplete event log unobserved events and their timestamps that are globally consistent with a PQR-system. We solve the problem by reconstructing unobserved traces of resources and queues according to the PQR-model and derive bounds for their timestamps using a linear program. While the problem is illustrated for material handling systems like baggage handling systems in airports, the approach can be applied to other settings where recording is incomplete. The ideas have been implemented in ProM and were evaluated using both synthetic and real-life event logs.

Analisis Pengendalian Kualitas Crude Palm Oil (CPO) PT. Kampar Tunggal Agrindo Dengan Menggunakan Statistical Process Control

Kampar Tunggal Agrindo merupakan perusahaan yang bergerak dibidang Pabrik Kelapa Sawit berskala 15 T/H berasal dari Kabupaten Kampar mengolah buah brondolan sawit menjadi minyak mentah (crude palm oil). Perusahaan ini mengalami ketidaksesuaian standart hasil produksi yang ditetapkan oleh perusahaan, dengan standar kadar asam < 30%, kadar air <0,50%, kadar kotoran <0,030%. Maka dari itu dibutuhkan analisis menggunakan metode statistical process control. Dari 3 parameter analisis ketidaksesuaian standart produk crude palm oil (CPO), diparamater kadar asam dan kadar air ada beberapa data yang out of control yang berarti tidak terkendali dan harus dilakukan analisis lebih lanjut. Dari 3 parameter kualitas produk CPO, maka yang menjadi prioritas untuk diperbaiki adalah parameter kadar air. Akar penyebab dari tingginya kadar air (> 0,50%) adalah manusia antara lain kurangnya inspeksi pada waktu perebusan akibatnya tekanan steam uap berlebihan sehingga suhu terlalu panas akibat kurang komunikasi antara operator boiler dan perebusan. Untuk itu perlu dilakukan pengawasan SOP dari pihak kepala produksi terhadap operator, penambahan unit material handling berupa loader dan merancang checklist preventif untuk mencegah kerusakan.

Application of Biomechanics Instrumentation in Occupational Health Research

Occupational morbidities during manual material handling operations are routine at workplaces. This is a global burden contributing substantially to the economy. The multifactorial etiology for musculoskeletal disorders (MSDs) along with workplace stressors require multidisciplinary preventive effort. Biomechanics plays a pivotal role in occupational health research quarrying into the root cause analysis of posture, load handling, muscular loading, balance, and stability at work. Sophisticated instrumentation and experimental techniques assist in understanding the biomechanical mechanisms of MSDs and ergonomic principles, etc. Kinetic, kinematic, isotonic, isokinetic, as well as isometric experimental modes investigate body postures and muscular responses. Foundation of biomechanics instrumentation and injury mechanism would aid researchers alongside ergonomists in dealing with identification, assessment, and control of workplace risks through participatory ergonomics approach. Judicious utilization of this discipline would approach a long-term sustainable solution to protect health and safety of workers at the workplace.

Circular Economy of Construction and Demolition Waste: A Literature Review on Lessons, Challenges, and Benefits

Conventionally, in a linear economy, C&D (Construction and Demolition) waste was considered as zero value materials, and, as a result of that, most C&D waste materials ended up in landfills. In recent years, with the increase in the awareness around sustainability and resource management, various countries have started to explore new models to minimize the use of limited resources which are currently overused, mismanaged, or quickly depleting. In this regard, the implementation of CE (Circular Economy) has emerged as a potential model to minimize the negative impact of C&D wastes on the environment. However, there are some challenges hindering a full transition to CE in the construction and demolition sectors. Therefore, this review paper aims to critically scrutinize different aspects of C&D waste and how CE can be integrated into construction projects. Reviewing of the literature revealed that the barriers in the implementation of CE in C&D waste sectors fall in five main domains, namely legal, technical, social, behavioral, and economic aspects. In this context, it was found that policy and governance, permits and specifications, technological limitation, quality and performance, knowledge and information, and, finally, the costs associated with the implementation of CE model at the early stage are the main barriers. In addition to these, from the contractors’ perspective, C&D waste dismantling, segregation, and on-site sorting, transportation, and local recovery processes are the main challenges at the start point for small-scale companies. To address the abovementioned challenges, and also to minimize the ambiguity of resulting outcomes by implementing CE in C&D waste sectors, there is an urgent need to introduce a global framework and a practicable pathway to allow companies to implement such models, regardless of their scale and location. Additionally, in this paper, recommendations on the direction for areas of future studies for a reduction in the environmental impacts have been provided. To structure an effective model approach, the future direction should be more focused on dismantling practices, hazardous material handling, quality control on waste acceptance, and material recovery processes, as well as a incentivization mechanism to promote ecological, economic, and social benefits of the CE for C&D sectors.

Optimizing Calibration Procedure to Train a Regression-Based Prediction Model of Actively Generated Lumbar Muscle Moments for Exoskeleton Control

The risk of low-back pain in manual material handling could potentially be reduced by back-support exoskeletons. Preferably, the level of exoskeleton support relates to the required muscular effort, and therefore should be proportional to the moment generated by trunk muscle activities. To this end, a regression-based prediction model of this moment could be implemented in exoskeleton control. Such a model must be calibrated to each user according to subject-specific musculoskeletal properties and lifting technique variability through several calibration tasks. Given that an extensive calibration limits the practical feasibility of implementing this approach in the workspace, we aimed to optimize the calibration for obtaining appropriate predictive accuracy during work-related tasks, i.e., symmetric lifting from the ground, box stacking, lifting from a shelf, and pulling/pushing. The root-mean-square error (RMSE) of prediction for the extensive calibration was 21.9 Nm (9% of peak moment) and increased up to 35.0 Nm for limited calibrations. The results suggest that a set of three optimally selected calibration trials suffice to approach the extensive calibration accuracy. An optimal calibration set should cover each extreme of the relevant lifting characteristics, i.e., mass lifted, lifting technique, and lifting velocity. The RMSEs for the optimal calibration sets were below 24.8 Nm (10% of peak moment), and not substantially different than that of the extensive calibration.