Dynamic Weighing of Non-Singulated Objects Using a Grid of Decoupled Platforms

Weighing systems exist in various sizes and forms to meet the persistent demand for measuring the mass of objects. Current solutions do not offer a system that can dynamically weigh packages moving in a non-singulated and non-spaced fashion, common in automated settings. In such environments, currently items are singulated which results in a slower flow, increased cost and space requirements. In this work, we propose a design in which small-sized conveyors are mounted on load cells in a grid formation to dynamically weigh non-singulated objects that meet some minimal spacing requirements between them. In the design, moving packages are tracked with a vision system, and an algorithm is formulated to estimate mass based on filtered load cell outputs. Each element of the grid is modelled as a mass-spring-damper system in order to simulate the expected load cell output for the moving objects. A discrete time-variant low-pass filter is adopted from literature to filter the signal and an algorithm is devised to produce a mass estimate. A parameter estimation technique and a simple averaging method which ignore transients are implemented as well for performance comparison. The results are verified experimentally in two proof-of-concept experiments for a full scale prototype. When tuned properly, the time-variant filter succeeds in giving an estimate within a mean of 0.02% error of the rated load cell capacity at speeds up to 0.6 m/s. This is good performance since it does not exceed the rated error for the load cells. The other two estimation methods fail to meet the accuracy requirement at speeds above 0.4 m/s. Potential design considerations and concerns are discussed. Further development and testing is required before the machine can become legal-for-trade

Assembly Line

An assembly line is a manufacturing process in which parts are added to a product in a sequential manner using optimally planned logistics to create a finished product in the fastest possible way. It is a flow-oriented production system where the productive units performing the operations, referred to as stations, are aligned in a serial manner. The present edited book is a collection of 12 chapters written by experts and well-known professionals of the field. The volume is organized in three parts according to the last research works in assembly line subject. The first part of the book is devoted to the assembly line balancing problem. It includes chapters dealing with different problems of ALBP. In the second part of the book some optimization problems in assembly line structure are considered. In many situations there are several contradictory goals that have to be satisfied simultaneously. The third part of the book deals with testing problems in assembly line. This section gives an overview on new trends, techniques and methodologies for testing the quality of a product at the end of the assembling line

Automated Manufacture of Fertilizing Agglomerates from Burnt Wood Ash

In Sweden, extensive research is conducted to find alternative sources of energy that should partly replace the electric power production from nuclear power. With the ambition to create a sustainable system for producing energy, the use of renewable energy is expected to grow further and biofuels are expected to account for a significant part of this increase. However, when biofuels are burned or gasified, ash appears as a by-product. In order to overcome the problems related to deposition in land fills, the idea is to transform the ashes into a product – agglomerates – that easily could be recycled back to the forest grounds; as a fertilizer, or as a tool to reduce the acidification in the forest soil at the spreading area. This work considers the control of a transformation process, which transforms wood ash produced at a district heating plant into fertilizing agglomerates. A robust machine, built to comply with the industrial requirements for continuous operation, has been developed and is controlled by an industrial control system in order to enable an automated manufacture

Diseño conceptual de un sistema de automatización para el control de flujo de cobre en una faja transportadora, cuyo límite de diseño son 9400 TPH

La minería forma parte de la historia del Perú, pues ha estado presente desde épocas preincaicas. Además, su aporte a la economía peruana es sustancial y equivalente al 10% del producto bruto interno del país, siendo uno de los pilares del desarrollo económico. Por otro lado, a nivel mundial, el Perú es considerado un gigante en la industria minera, ya que está presente en el podio de países con mayor reserva de minerales como oro, zinc y cobre. Con el fin de tener un mayor aprovechamiento de estas reservas es necesario un marco tecnológico que incentive el desarrollo de este sector. El presente trabajo surge como una pequeña contribución al desarrollo en este campo y busca solucionar, desde un punto de vista conceptual, un problema real obtenido de una empresa minera, persiguiendo el objetivo de aumentar los índices de producción y reducir las mermas. El problema a resolver es el flujo no controlado en una faja transportadora. Se investigan y comparan diversas tecnologías para finalmente llegar a un concepto de solución.Trabajo de investigació

Gain tuning of proportional integral controller based on multiobjective optimization and controller hardware-in-loop microgrid setup

Proportional integral (PI) control is a commonly used industrial controller framework. This PI controller needs to be tuned to obtain desired response from the process under control. Tuning methods available in literature by and large need sophisticated mathematical modelling, and simplifications in the plant model to perform gain tuning. The process of obtaining approximate plant model conceivably become time consuming and produce less accurate results. This is due to the simplifications desired by the power system applications especially when power electronics based inverters are used in it. Optimal gain selection for PI controllers becomes crucial for microgrid application. Because of the presence of inverter based distributed energy resources. In the proposed approach, a multi-objective genetic algorithm is used to tune the controller to obtain expected step response characteristics. The proposed approach do not need simplified mathematical models. This prevents the need for obtaining unfailing plant models to maintain the fidelity of modelling. Microgrid system and the PI controller are modelled in different software, hardware platform and tuned using the proposed approach. Gain values for PI controller in these different platform are tuned using the same objective function and multi-objective optimization. This proves the re-usability, scalability, and modularity of the proposed tuning algorithm. Three different combination of software, hardware platform are proposed. First, the process and the PI controller are modelled in a computer based hardware. In order to increase the speed of the multi-objective optimization in the computer based hardware parallel computing is employed. This is a natural fit for paralleling the GA based optimization. Second, both the plant and control representation are modelled in the real time digital simulator (RTDS). Finally, a controller hardware in loop platform is used. In this platform, the plant will be modelled in RTDS and the PI controller will be modelled in an FPGA based hardware platform. Results indicate that the proposed approach has promising potentials since it does not need to simplify the switching model and can effectively solve the complicated tuning procedure using parallel computing. Similar advantage could be said for RTDS based tuning because RTDS simulates the models in real time

Soft Computing Techniques and Their Applications in Intel-ligent Industrial Control Systems: A Survey

Soft computing involves a series of methods that are compatible with imprecise information and complex human cognition. In the face of industrial control problems, soft computing techniques show strong intelligence, robustness and cost-effectiveness. This study dedicates to providing a survey on soft computing techniques and their applications in industrial control systems. The methodologies of soft computing are mainly classified in terms of fuzzy logic, neural computing, and genetic algorithms. The challenges surrounding modern industrial control systems are summarized based on the difficulties in information acquisition, the difficulties in modeling control rules, the difficulties in control system optimization, and the requirements for robustness. Then, this study reviews soft-computing-related achievements that have been developed to tackle these challenges. Afterwards, we present a retrospect of practical industrial control applications in the fields including transportation, intelligent machines, process industry as well as energy engineering. Finally, future research directions are discussed from different perspectives. This study demonstrates that soft computing methods can endow industry control processes with many merits, thus having great application potential. It is hoped that this survey can serve as a reference and provide convenience for scholars and practitioners in the fields of industrial control and computer science

Modern approaches to control of a multiple hearth furnace in kaolin production

The aim of this thesis is to improve the overall efficiency of the multiple hearth furnace (MHF) in kaolin calcination by developing control strategies which incorporate machine learning based soft sensors to estimate mineralogy related constraints in the control strategy. The objective of the control strategy is to maximize the capacity of the furnace and minimize energy consumption while maintaining the product quality of the calcined kaolin. First, the description of the process of interest is given, highlighting the control strategy currently implemented at the calciner studied in this work. Next, the state of the art on control of calcination furnaces is presented and discussed. Then, the description of the mechanistic model of the MHF, which plays a key role in the testing environment, is provided and an analysis of the MHF dynamic behavior based on the industrial and simulated data is presented. The design of the mineralogy-driven control strategy for the multiple hearth furnace and its implementation in the simulation environment are also outlined. The analysis of the results is then presented. Furthermore, the extensive sampling campaign for testing the soft sensors and the control strategy logic of the industrial MHF is reported, and the results are analyzed and discussed. Finally, an introduction to Model Predictive Control (MPC) is presented, the design of the Linear MPC framework for the MHF in kaolin calcination is described and discussed, and future research is outlined

Transportation system selection in open-pit mines (Truck-Shovel and IPCC systems) based on the technical, economic, environmental, safety, and social (TEcESaS) indexes

The production of raw materials through mining projects is nowadays very challenging, mainly due to the rapid progress in the industrial and technological fields. On the one hand, they have to fulfill industries' requirements in their demand for materials while making a profit based on the current technologies. On the other hand, they should consider all other limitations, primarily environmental and social challenges that are confronting. The transportation system in any mining project is one of the most significant parts, especially in the technical and economic issues. It must transfer the planned volume of ore/waste that the whole stream of the mining process would not be interrupted and, it can cover the technical challenges and the costs imposed on the project. Additionally, it should be designed and selected to have the lowest environmental impact and the highest safety during the operation. Accordingly, a transportation system selection process that considers all these factors is one of the challenging issues in any mining project. Although the Truck-Shovel system is known as the conventional transportation in open-pit mines, which is preferable because of the low capital cost and high flexibility, it still imposes a high rate of operating costs, safety issues as well as environmental footprints. In-Pit Crushing and Conveying (IPCC) systems are the alternative transportation systems for the Truck-Shovel systems, in which the material is crushed inside the mine’s pit limit and transferred into the outside through conveyor belts. Although these systems are not new, they are mostly neglected as a transportation option basically due to the high capital cost and low flexibility. On the contrary, they can offer more environmentally friendly and safer working areas and a lower operating cost. According to these facts, each transportation system is preferable in a couple of technical, economic, environmental, safety, and social issues. Accordingly, in each circumstance, one or more of these systems can be used in the mining project. However, there is not yet a way or tool that investigates the transportation system selection along with the mine life that takes into account all of these factors. To fill this gap, this project aims to define a model to introduce all these elements while it is interactively connected throughout the mine life. For this and as the first step, the system dynamics modeling is defined and used to build the model for all the technical, economic, environmental, safety, and social factors. As an output of this step, software entitled “TEcESaS Indexes” is designed and produced through Venapp that makes working with the model comfortable. As the second step, a selection method based on the Analytical Hierarchy Process (AHP) is performed that the transportation system selection regarding all the mentioned factors can be made. As the output in this step, the “Sustainability Index” software programmed in the Java language is developed. Considering a hypothetical copper open-pit mine as the case study and implementing the designed software, the results show although the Truck-Shovel system should be used in the first two years of the project (2016 and 2017) in the single expert and deterministic mode, the Fully Mobile In-Pit Crushing and Conveying (FMIPCC) system shows the highest sustainability index among other transportation systems from 2018 until the end of the mine life. While in the group decision making and deterministic simulation, the Truck-Shovel system should be utilized from 2016 to 2020. Additionally, in the group decision making and stochastic mode, the FMIPCC is the selected transportation system with the highest sustainability index probability

Condition monitoring of pharmaceutical powder compression during tabletting using acoustic emission

This thesis was submitted for the degree of Doctor of Philosophy and awarded by Brunel University.This research project aimed to develop a condition monitoring system for the final production quality of pharmaceutical tablets and detection capping and lamination during powder compression process using the acoustic emission (AE) method. Pharmaceutical tablet manufacturers obliged by regulatory bodies to test the tablet's physical properties such as hardness, dissolution and disintegration before the tablets are released to the market. Most of the existing methods and techniques for testing and monitoring these tablet's properties are performed at the tablet post-compression stage. Furthermore, these tests are destructive in nature. Early experimental investigations revealed that the AE energy that is generated during powder compression is directly proportional to the peak force that is required to crush the tablet, i. e. crushing strength. Further laboratory and industrial experimental investigation have been conducted to study the relationship between the AE signals and the compression conditions. Traditional AE signal features such as energy, count, peak amplitude, average signal level, event duration and rise time were recorded. AE data analysis with the aid of advanced classification algorithm, fuzzy C-mean clustering showed that the AE energy is a very useful parameter in tablet condition monitoring. It was found that the AE energy that is generated during powder compression is sensitive to the process and is directly proportional to the compression speed, particle size, homogeneity of mixture and the amount of material present. Also this AE signal is dependent upon the type of material used as the tablet filler. Acoustic emission has been shown to be a useful technique for characterising some of the complex physical changes which occur during tabletting. Capping and lamination are serious problems that are encountered during tabletting. A capped or laminated tablet is one which no longer retains its mechanical integrity and exhibit low strength characteristics. Capping and lamination can be caused by a number of factors such as excessive pressure, insufficient binder in the granules and poor material flowabilities. However, capping and lamination can also occur randomly and they are also dependent upon the material used in tabletting. It was possible to identify a capped or laminated tablet by monitoring the AE energy level during continuous on-line monitoring of tabletting. Capped tablets indicated by low level of AE energy. The proposed condition monitoring system aimed to set the AE energy threshold that could discriminate between capped and non-capped tablets. This was based upon statistical distributions of the AE energy values for both the capped and non-capped tablets. The system aims to minimise the rate of false alarms (indication of capping when in reality capping has not occurred) and the rate of missed detection (an indication of non capping, when in reality capping has occurred). A novel approach that employs both the AE method and the receiver operating characteristic (ROC) curve was proposed for the on-line detection of capping and lamination during tabletting. The proposed system employs AE energy as the discriminating parameter to detect between capped and non-capped tablets. The ROC curve was constructed from the area under the two distributions of both capped and non-capped tablet. This curve shows a trade-off between the probabilities of true detection rate and false alarm rate for capped and non-capped tablet. A two-graph receiver operating characteristic (ROC) curve was presented as a modification of the original ROC curve to enable an operator to directly select the desired energy threshold for tablet monitoring. This plot shows the ROC co-ordinate as a function of the threshold value over the entire threshold (AE energy) range for all test outcomes. An alternative way of deciding a threshold based on the slope of the ROC curve was also developed. The slope of the ROC curve represents the optimal operating point on the curve. It depends upon the penalties cost of capping and the prevalence of capping. Sets of guidelines have been outlined for decision making i.e. threshold setting. These guidelines take into account both the prevalence of capping in manufacturing and the cost associated with various outcomes of tablet formation. The proposed condition monitoring system also relates AE monitoring to non-AE measurement as it enable an operator predicting tablet hardness and disintegration form the AE energy, a relationship which was established in this research