Search results for: Industrial engineering

Authors: Petcharat  Kerdonfag, Surasak Taneepanichskul, Winai Wadwongtham

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Industrial noise is usually considered as the main impact of the environmental health and safety because its exposure can cause permanently serious hearing damage. Despite providing strictly hearing protection standards and campaigning extensively encouraging public health awareness among industrial workers in Thailand, hazard noise-induced hearing loss has dramatically been massive obstacles for workers’ health. The aims of the study were to explore and specify the hearing threshold levels among steel industrial workers responsible in which higher noise levels of work zone and to examine the relationships of hearing loss and workers’ age and the length of employment in Samut Prakan province, Thailand. Cross-sectional study design was done. Ninety-three steel industrial workers in the designated zone of higher noise (> 85dBA) with more than 1 year of employment from two factories by simple random sampling and available to participate in were assessed by the audiometric screening at regional Samut Prakan hospital. Data of doing screening were collected from October to December, 2016 by the occupational medicine physician and a qualified occupational nurse. All participants were examined by the same examiners for the validity. An Audiometric testing was performed at least 14 hours after the last noise exposure from the workplace. Workers’ age and the length of employment were gathered by the developed occupational record form. Results: The range of workers’ age was from 23 to 59 years, (Mean = 41.67, SD = 9.69) and the length of employment was from 1 to 39 years, (Mean = 13.99, SD = 9.88). Fifty three (60.0%) out of all participants have been exposing to the hazard of noise in the workplace for more than 10 years. Twenty-three (24.7%) of them have been exposing to the hazard of noise less than or equal to 5 years. Seventeen (18.3%) of them have been exposing to the hazard of noise for 5 to 10 years. Using the cut point of less than or equal to 25 dBA of hearing thresholds, the average means of hearing thresholds for participants at 4, 6, and 8 kHz were 31.34, 29.62, and 25.64 dB, respectively for the right ear and 40.15, 32.20, and 25.48 dB for the left ear, respectively. The more developing age of workers in the work zone with hazard of noise, the more the hearing thresholds would be increasing at frequencies of 4, 6, and 8 kHz (p =.012, p =.026, p =.024) for the right ear, respectively and for the left ear only at the frequency 4 kHz (p =.009). Conclusion: The participants’ age in the hazard of noise work zone was significantly associated with the hearing loss in different levels while the length of participants’ employment was not significantly associated with the hearing loss. Thus hearing threshold levels among industrial workers would be regularly assessed and needed to be protected at the beginning of working.

Keywords: hearing threshold levels, hazard of noise, hearing loss, audiometric testing

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Authors: Kashif Ahmed

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Recent years researchers have been motivated towards extensive exploring of living organism, which could be utilized effectively in intense industrial conditions. The present study shows enhanced production, purification and characterization of industrial enzyme, invertase (Beta-D-fructofuranosidase) from Penicillium lilacinum. Various agricultural based by-products (cotton stalk, sunflower waste, rice husk, molasses and date syrup) were used as energy source. The highest amount of enzyme (13.05 Units/mL) was produced when the strain was cultured on growth medium containing date syrup as energy source. Yeast extract was used as nitrogen source after 96 h of incubation at incubation temperature of 40º C. Initial pH of medium was 8.0, inoculum size 6x10⁶ conidia and 200 rev/min agitation rate. The enzyme was also purified (7 folds than crude) and characterized. Molecular mass of purified enzyme (65 kDa) was determined by 10 % SDS-PAGE. Lineweaver-Burk Plot was used to determine Kinetic constants (Vmax 178.6 U/mL/min and Km 2.76 mM). Temperature and pH optima were 55º C and 5.5 respectively. MnCl₂ (52.9 %), MgSO₄ (48.9 %), BaCl₂ (24.6 %), MgCl₂ (9.6 %), CoCl₂ (5.7 %) and NaCl (4.2 %) enhanced the relative activity of enzyme and HgCl₂ (-92.8 %), CuSO₄ (-80.2 %) and CuCl₂ (-76.6 %) were proved inhibitors. The strain was showing enzyme activity even at extreme conditions of temperature (up to 60º C) and pH (up to 9), so it can be used in industries.

Keywords: invertase, Penicillium lilacinum, submerged fermentation, industrial enzyme

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Authors: Sahra Setorg

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The purpose of this study was to determine the effect of meta-cognitive therapy on meta-cognitive defects and emotional regulation in industrial substance dependence patients. This quasi-experimental research was conducted with post-test and two-month follow-up design with control and experimental groups. The statistical population consisted of all industrial Substance dependence patients refer to addictive withdrawal clinics in Esfahan city, in Iran in 2013. 45 patients were selected from three clinics through the convenience sampling method and were randomly divided into two experimental groups (15 crack dependences, 15 amphetamine dependences) and one control group (n=15). The meta-cognitive questionnaire (MCQ) and difficulties in emotional regulation questionnaire (DERS) were used as pre-test measures and the experimental groups (crack and amphetamine) received 8 MC therapy sessions in groups. The data were analyzed via multivariate covariance statistic method by spss-18. The results showed that MCT had a significant effect in improving the meta-cognitive defects in crack and amphetamine dependences. Also, this therapy can increase the emotional regulation in both groups (p<0/05).The effect of this therapy is confirmed in two months followup. According to these findings, met-cognitive is as an interface and important variable in prevention, control, and treatment of the new industrial substance dependences.

Keywords: meta-cognitive therapy, meta-cognitive defects, emotional regulation, substance dependence disorder

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Authors: G. Wimmers

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The University of Northern British Columbia needed a new laboratory building for the Master of Engineering in Integrated Wood Design Program and its new Civil Engineering Program. Since the University is committed to reducing its environmental footprint and because the Master of Engineering Program is actively involved in research of energy efficient buildings, the decision was made to request the energy efficiency of the Passive House Standard in the Request for Proposals. The building is located in Prince George in Northern British Columbia, a city located at the northern edge of climate zone 6 with an average low between -8 and -10.5 in the winter months. The footprint of the building is 30m x 30m with a height of about 10m. The building consists of a large open space for the shop and laboratory with a small portion of the floorplan being two floors, allowing for a mezzanine level with a few offices as well as mechanical and storage rooms. The total net floor area is 1042m² and the building’s gross volume 9686m³. One key requirement of the Passive House Standard is the airtight envelope with an airtightness of < 0.6 ach@50Pa. In the past, we have seen that this requirement can be challenging to reach for industrial buildings. When testing for air tightness, it is important to test in both directions, pressurization, and depressurization, since the airflow through all leakages of the building will, in reality, happen simultaneously in both directions. A specific detail or situation such as overlapping but not sealed membranes might be airtight in one direction, due to the valve effect, but are opening up when tested in the opposite direction. In this specific project, the advantage was the overall very compact envelope and the good volume to envelope area ratio. The building had to be very airtight and the details for the windows and doors installation as well as all transitions from walls to roof and floor, the connections of the prefabricated wall panels and all penetrations had to be carefully developed to allow for maximum airtightness. The biggest challenges were the specific components of this industrial building, the large bay door for semi-trucks and the dust extraction system for the wood processing machinery. The testing was carried out in accordance with EN 132829 (method A) as specified in the International Passive House Standard and the volume calculation was also following the Passive House guideline resulting in a net volume of 7383m3, excluding all walls, floors and suspended ceiling volumes. This paper will explore the details and strategies used to achieve an airtightness of 0.07 ach@50Pa, to the best of our knowledge the lowest value achieved in North America so far following the test protocol of the International Passive House Standard and discuss the crucial steps throughout the project phases and the most challenging details.

Keywords: air changes, airtightness, envelope design, industrial building, passive house

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Authors: Anastasia Stamatiou, Markus Odermatt, Dominic Leemann, Ludger J. Fischer, Joerg Worlitschek

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The successful integration of thermal energy storage in industrial processes is expected to play an important role in the energy turnaround. Latent heat storage technologies can offer more compact thermal storage at a constant temperature level, in comparison to conventional, sensible thermal storage technologies. The focus of this study is the development of latent heat storage solutions based on the Phase Change Slurry (PCS) concept. Such systems promise higher energy densities both as refrigerants and as storage media while presenting better heat transfer characteristics than conventional latent heat storage technologies. This technology is expected to deliver high thermal power and high-temperature stability which makes it ideal for storage of process heat. An evaluation of important batch processes in industrial applications set the focus on materials with a melting point in the range of 55 - 90 °C. Aluminium ammonium sulfate dodecahydrate (NH₄Al(SO₄)₂·12H₂O) was chosen as the first interesting PCM for the next steps of this study. The ability of this material to produce slurries at the relevant temperatures was demonstrated in a continuous mode in a laboratory test-rig. Critical operational and design parameters were identified.

Keywords: esters, latent heat storage, phase change materials, thermal properties

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Authors: Vivek Anand, Rainer Naegele

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Industry 4.0 envisages 'smart' manufacturing and services, taking the automation of the 3rd Industrial Revolution to the autonomy of the 4th Industrial Revolution. Powered by innovations in technology and business models, this disruptive transformation is revitalising industry by integrating silos across and beyond value chains. Motivated by the challenges faced by SMEs and Startups in understanding and adopting Industry 4.0, this paper aims to analyse the concept of Growth Poles and evaluate the possibility of its application to Innovation Clusters that strive to propel Industry 4.0 adoption and capacity building. The proposed paper applies qualitative research methodologies including focus groups and survey questionnaires to identify the various factors that affect formation and development of Innovation Clusters. Employing content analysis, the interaction between SMEs and other ecosystem players in such clusters is studied. A strong collaborative culture is a key driver of digital transformation and technology adoption across sectors, value chains and supply chains; and will position these cluster-based growth poles at the forefront of industrial renaissance. Motivated by this argument, and based on the results of the qualitative research, a roadmap will be proposed to position Innovation Clusters as Growth Poles and effective ecosystems to support Industry 4.0 adoption in a region in the medium to long term. This paper will contribute to the current understanding of the role of Innovation Clusters in capacity building. Relevant management and policy implications stem from the analysis. Furthermore, the findings will be helpful for academicians and policymakers alike, who can leverage an ‘innovation cluster policy’ to enable Industry 4.0 Growth Poles in their regions.

Keywords: digital transformation, fourth industrial revolution, growth poles, industry 4.0, innovation clusters, innovation policy, SMEs and startups

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Authors: Y. Kourd, D. Lefebvre, N. Guersi

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The monitoring of industrial processes is required to ensure operating conditions of industrial systems through automatic detection and isolation of faults. In this paper we propose a method of fault diagnosis based on neuro-fuzzy technique and the choice of a threshold. The validation of this method on a test bench "Actuator Electro DAMADICS Benchmark". In the first phase of the method, we construct a model represents the normal state of the system to fault detection. With residuals analysis generated and the choice of thresholds for signatures table. These signatures provide us with groups of non-detectable faults. In the second phase, we build faulty models to see the flaws in the system that are not located in the first phase.

Keywords: residuals analysis, threshold, neuro-fuzzy system, residual evaluation

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Authors: Semanur Savruk, Onur Akbatı

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Integration of various communication protocols into an automation system causes a rise in setup and maintenance cost and make to control network devices in difficulty. The gateway becomes necessary for reducing complexity in network topology. In this study, Modbus RTU/Modbus TCP industrial ethernet gateway design and implementation are presented with ARM embedded system and FreeRTOS real-time operating system. The Modbus gateway can perform communication with Modbus RTU and Modbus TCP devices over itself. Moreover, the gateway can be adjustable with the user-interface application or messaging interface. Conducted experiments and the results are presented in the paper. Eventually, the proposed system is a complete, low-cost, real-time, and user-friendly design for monitoring and setting devices and useful for meeting remote control purposes.

Keywords: gateway, industrial communication, modbus, network

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Authors: Deonie Botha

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Digital transformation and the digitization of occupational health and safety training have grown exponentially due to a variety of contributing factors. The literature suggests that digitalization has numerous benefits but also has associated challenges. The aim of the paper is to develop an understanding of both the perceived benefits and challenges of digitalization in an occupational health and safety context in an effort to design and develop e-learning interventions that will optimize the benefits of digitalization and address the associated challenges. The paper proposes, deliberate and tests the design principles of an e-learning intervention to ensure alignment with the requirements of a digitally transformed environment. The results of the research are based on a literature review regarding the requirements and effect of the Fourth Industrial Revolution on learning and e-learning in particular. The findings of the literature review are enhanced with empirical research in the form of a case study conducted in an organization that designs and develops e-learning content in the occupational health and safety industry. The primary findings of the research indicated that: (i) The requirements of learners and organizations in respect of e-learning are different than previously (i.e., a pre-Fourth Industrial Revolution related work setting). (ii) The design principles of an e-learning intervention need to be aligned with the entire value chain of the organization. (iii) Digital twins support and enhance the design and development of e-learning. (iv)Learning should incorporate a multitude of sensory experiences and should not only be based on visual stimulation. (v) Data that are generated as a result of e-learning interventions should be incorporated into big data streams to be analyzed and to become actionable. It is therefore concluded that there is general consensus on the requirements that e-learning interventions need to adhere to in a digitally transformed occupational health and safety work environment. The challenge remains for organizations to incorporate data generated as a result of e-learning interventions into the digital ecosystem of the organization.

Keywords: digitalization, training, fourth industrial revolution, big data

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Authors: Aiman Alshare, Sahar Qaadan

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A curvature dependent force correction algorithm for planning force controlled grinding process with off-line programming flexibility is designed for ABB industrial robot, in order to avoid the manual interface during the process. The machining path utilizes a spline curve fit that is constructed from the CAD data of the workpiece. The fitted spline has a continuity of the second order to assure path smoothness. The implemented algorithm computes uniform forces normal to the grinding surface of the workpiece, by constructing a curvature path in the spatial coordinates using the spline method.

Keywords: ABB industrial robot, grinding process, offline programming, CAD data extraction, force correction algorithm

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Authors: Robert Höttger, Lukas Krawczyk, Burkhard Igel

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This paper introduces novel approaches to partitioning and mapping in terms of model-based embedded multicore system engineering and further discusses benefits, industrial relevance and features in common with existing approaches. In order to assess and evaluate results, both approaches have been applied to a real industrial application as well as to various prototypical demonstrative applications, that have been developed and implemented for different purposes. Evaluations show, that such applications improve significantly according to performance, energy efficiency, meeting timing constraints and covering maintaining issues by using the AMALTHEA platform and the implemented approaches. Further- more, the model-based design provides an open, expandable, platform independent and scalable exchange format between OEMs, suppliers and developers on different levels. Our proposed mechanisms provide meaningful multicore system utilization since load balancing by means of partitioning and mapping is effectively performed with regard to the modeled systems including hardware, software, operating system, scheduling, constraints, configuration and more data.

Keywords: partitioning, mapping, distributed systems, scheduling, embedded multicore systems, model-based, system analysis

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Authors: Shiuh-Jer Huang, Chen-Zon Yan, C. K. Huang, Chun-Chien Ting

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Since the vision system application in industrial environment for autonomous purposes is required intensely, the image recognition technique becomes an important research topic. Here, deep learning algorithm is employed in image system to recognize the industrial object and integrate with a 7A6 Series Manipulator for object automatic gripping task. PC and Graphic Processing Unit (GPU) are chosen to construct the 3D Vision Recognition System. Depth Camera (Intel RealSense SR300) is employed to extract the image for object recognition and coordinate derivation. The YOLOv2 scheme is adopted in Convolution neural network (CNN) structure for object classification and center point prediction. Additionally, image processing strategy is used to find the object contour for calculating the object orientation angle. Then, the specified object location and orientation information are sent to robotic controller. Finally, a six-axis manipulator can grasp the specific object in a random environment based on the user command and the extracted image information. The experimental results show that YOLOv2 has been successfully employed to detect the object location and category with confidence near 0.9 and 3D position error less than 0.4 mm. It is useful for future intelligent robotic application in industrial 4.0 environment.

Keywords: deep learning, image processing, convolution neural network, YOLOv2, 7A6 series manipulator

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Authors: Zhanara Suleimenova, Raushan Blieva, Aigerim Zhakipbekova, Inkar Tapenbayeva, Zhanar Narmuratova

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Green processes are based on innovative technologies that do not negatively affect the environment. Industrial enzymes originated from biological systems can effectively contribute to sustainable development through being isolated from microorganisms which are fermented using primarily renewable resources. Many widespread microorganisms secrete a significant amount of biocatalysts into the environment, which greatly facilitates the task of their isolation and purification. The ability to control the enzyme production through the regulation of their biosynthesis and the selection of nutrient media and cultivation conditions allows not only to increase the yield of enzymes but also to obtain enzymes with certain properties. In this regard, large potentialities are embedded in immobilized cells. Enzyme production technology in a secreted active form enabling industrial application on an economically feasible scale has been developed. This method is based on the immobilization of enzyme producers on a solid career. Immobilizing has a range of advantages: decreasing the price of the final product, absence of foreign substances, controlled process of enzyme-genesis, the ability of various enzymes' simultaneous production, etc. Design of proposed equipment gives the opportunity to increase the activity of immobilized cell culture filtrate comparing to free cells, growing in periodic culture conditions. Such technology allows giving a 10-times raise in culture productivity, to prolong the process of fungi cultivation and periods of active culture liquid generation. Also, it gives the way to improve the quality of filtrates (to make them more clear) and exclude time-consuming processes of recharging fermentative vials, that require manual removing of mycelium.

Keywords: industrial enzymes, immobilization, submerged fermentation, microscopic fungi

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Authors: Lilian Ogechi Iheukwumere-Esotu, Akilu Yunusa-Kaltungo, Paul Chan

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Industrial assets are prone to degradation and eventual failures due to repetitive loads and harsh environments in which they operate. These failures often lead to costly downtimes, which may involve loss of critical assets and/or human lives. The rising pressures from stakeholders for optimized systems’ outputs have further placed strains on business organizations. Traditional means of combating such failures are by adopting strategies capable of predicting, controlling, and/or reducing the likelihood of systems’ failures. Turnarounds, shutdowns, and outages (TSOs) projects are popular maintenance management activities conducted over a certain period of time. However, despite the critical and significant cost implications of TSOs, the management of the interface of knowledge between academia and industry to our best knowledge has not been fully explored in comparison to other aspects of industrial operations. This is perhaps one of the reasons for the limited knowledge transfer between academia and industry, which has affected the outcomes of most TSOs. Prior to now, the study of knowledge development trends as a failure analysis tool in the management of TSOs projects have not gained the required level of attention. Hence, this review provides useful references and their implications for future studies in this field. This study aims to harmonize the existing research trends of TSOs through a systematic review of more than 3,000 research articles published over 7 decades (1940- till date) which were extracted using very specific research criteria and later streamlined using nominated inclusion and exclusion parameters. The information obtained from the analysis were then synthesized and coded into 8 parameters, thereby allowing for a transformation into actionable outputs. The study revealed a variety of information, but the most critical findings can be classified into 4 folds: (1) Empirical validation of available conceptual frameworks and models is still a far cry in practice, (2) traditional project management views for managing uncertainties are still dominant, (3) Inconsistent approaches towards the adoption and promotion of knowledge management systems which supports creation, transfer and application of knowledge within and outside the project organization and, (4) exploration of social practices in industrial maintenance project environments are under-represented within the existing body of knowledge. Thus, the intention of this study is to depict the usefulness of a framework which incorporates fact findings emanating from careful analysis and illustrations of evidence based results as a suitable approach which can tackle reoccurring failures in industrial maintenance projects.

Keywords: industrial maintenance, knowledge management, maintenance projects, systematic review, TSOs

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Authors: Tudor Deaconescu, Andrea Deaconescu

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Deployment of pneumatic muscles in various industrial applications is still in its early days, considering the relative newness of these components. The field of robotics holds particular future potential for pneumatic muscles, especially in view of their specific behaviour known as compliance. The paper presents and discusses an innovative constructive solution for a gripper system mountable on an industrial robot, based on actuation by a linear pneumatic muscle and transmission of motion by gear and rack mechanism. The structural, operational and constructive models of the new gripper are presented, along with some of the experimental results obtained subsequently to the testing of a prototype. Further presented are two control variants of the gripper system, one by means of a 3/2-way fast-switching solenoid valve, the other by means of a proportional pressure regulator. Advantages and disadvantages are discussed for both variants.

Keywords: gripper system, pneumatic muscle, structural modelling, robotics

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Authors: D. I. Akintayo, C. O. Aje

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This study investigated the moderating influence of gender difference and conflict resolution strategy preference on managers` efficiency in managing industrial conflict in work organizations in South-Western Nigeria. This was for the purpose of ascertaining the relevance of gender difference and conflict resolution strategy preference to managerial efficiency towards ensuring sustainable industrial peace and harmonious labour-management relations at workplaces in Nigeria. Descriptive ex-post-facto research design was adopted for the study. A total of 185 respondents were selected for the study using purposive stratified sampling technique. A set of questionnaire titled ‘Rahim Organizational Conflict Inventory’ (ROCI) and Managerial Conflict Efficiency Scale (MCES) were adopted for the study. The three generated hypotheses were tested using Pearson Product Moment Correlation and t-test statistical methods. The findings of the study revealed that: A significant relationship exists between gender difference and conflict management preference of the managers(r = 0.644; P < 0.05). I t was also found that there was no significant difference between male and female managers’ conflict management strategy preference (t (181) = 11.08; P > 0.05).The finding reveals that there is no significant difference between female and male managers’ conflict management efficiency on the basis of conflict management preference of the managers (t (181) = 10.23; P > 0.05). Based on the findings of the study, it is recommended that collective bargaining strategy should be encouraged as conflict resolution strategy in order to guarantee effective management of industrial conflict and harmonious labour-management relations. Also, both male and female managers should be empowered to be appointed to managerial positions and should avoid the use of coercion, competition, aggressiveness and pro-task in the course of managing industrial conflict. Rather, persuasion, compromising, relational, lobbying and participatory approaches should be employed during collective bargaining process in order to foster effective management of conflict at workplaces.

Keywords: conflict management, gender difference, managerial studies, public organization and managers, strategy preference

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Authors: Ana Belon Hercilla

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The study is developed in “Reactivos Jeans” company, in the city of Arequipa, whose main business is the laundry of garments at an industrial level. In 2012 the company initiated actions to provide a dry cleaning service of alpaca fiber garments, recognizing that this item is in a growth phase in Peru. Additionally this company took the initiative to use a new greenwashing technology which has not yet been developed in the country. To accomplish this, a redesign of both the process and the plant layout was required. For redesigning the plant, the methodology used was the Systemic Layout Planning, allowing this study divided into four stages. First stage is the information gathering and evaluation of the initial situation of the company, for which a description of the areas, facilities and initial equipment, distribution of the plant, the production process and flows of major operations was made. Second stage is the development of engineering techniques that allow the logging and analysis procedures, such as: Flow Diagram, Route Diagram, DOP (process flowchart), DAP (analysis diagram). Then the planning of the general distribution is carried out. At this stage, proximity factors of the areas are established, the Diagram Paths (TRA) is developed, and the Relational Diagram Activities (DRA). In order to obtain the General Grouping Diagram (DGC), further information is complemented by a time study and Guerchet method is used to calculate the space requirements for each area. Finally, the plant layout redesigning is presented and the implementation of the improvement is made, making it possible to obtain a model much more efficient than the initial design. The results indicate that the implementation of the new machinery, the adequacy of the plant facilities and equipment relocation resulted in a reduction of the production cycle time by 75.67%, routes were reduced by 68.88%, the number of activities during the process were reduced by 40%, waits and storage were removed 100%.

Keywords: redesign, time optimization, industrial laundry, greenwashing

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Authors: Pranab Kumar Goswami, Elena Gurung

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Small and medium enterprises (SME) are considered as the driving force for the economic growth of a developing country like India. Most of the SMEs are located in residential/non-industrial areas to avoid legal obligations of occupational safety and health (OSH) provisions. This study was conducted in Delhiwith a view to analyze the accidents that occurredduringthe year 2019 & 2020. The objective of the study was to find out the accident prone SMEs in Delhi and major causes of such accidents. Methods: Survey and comprehensive data analysis methods, followed by applying simple statistical techniques, were used for this study. The accident reports for the study period collected from the labour department and police stations were analyzed for the study. The injured workers were interviewed to ascertain safety compliances, training and awareness programs, etc. The study was completed in March2021. Results: It was found that most of the accidents took place in SMEs located in residential/non- industrial areas in Delhi. The accident-prone machines were found to be power presses (42%) and injection moulding machines (37%). Predominantly unsafe machinery or unsafe working conditions and lack of training of worker were observed to be the major causes of accidents in such industries. Conclusions: It was concluded from the study that unsafe machinery/equipment and lack of proper training to the workers were two main reasons for increase in accidents.It was also concluded that the industries located in industrial areas were better placed in terms of workplace compliances. The managements who were running their operations from residential/non-industrial areaswere found to be less aware on health and safety issues. Lack of enforcement by government agencies in such areas has escalated this problem. Adequate training to workers, managing safe & healthy workplace, and sustained enforcement can reduce accidents in such industries.

Keywords: SME, accident prevention, cause of accident, unorganised

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Authors: Mario Sergio de Andrade Zago, Javier Mazariegos Pablos, Eduvaldo Paulo Sichieri

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This research project accomplished a study on the technical feasibility of recycling industrial solid waste generated by the discharge of casting sand agglomeration with clay, blast furnace slag and sugar cane bagasse ash. For this, the plan proposed a methodology that initially establishes a process of solid waste encapsulation, by using solidification/stabilization technique on Portland cement matrices, in which the residuals act as small and large aggregates on the composition of concrete, and later it presents the possibility of using this concrete in the manufacture of concrete pieces (concrete blocks) for paving. The results obtained in this research achieved the objective set with great success, regarding the manufacturing of concrete pieces (blocks) for paving urban roads, whenever there is special vehicle traffic or demands capable of producing accentuated abrasion effects (surpassing the 50 MPa required by the regulation), which probes the technical practicability of using waste from sand casting agglomeration with clay and blast furnace slag used in this study, unlocking usage possibilities for construction.

Keywords: industrial solid waste, solidification/stabilization, Portland cement, reuse, bagasse ash in the sugar cane, concrete

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Authors: Joseph Lillington, Tom Gout, Mike Harrison, Ian Farnan

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The vitrification of high-level nuclear waste within borosilicate glass and its incorporation within a multi-barrier repository deep underground is widely accepted as the preferred disposal method. However, for this to happen, any safety case will require validation that the initially localized radionuclides will not be considerably released into the near/far-field. Therefore, accurate mechanistic models are necessary to predict glass dissolution, and these should be robust to a variety of incorporated waste species and leaching test conditions, particularly given substantial variations across international waste-streams. Here, machine learning is used to predict glass material properties (viscosity, density) and glass leaching model parameters from large-scale industrial data. A variety of different machine learning algorithms have been compared to assess performance. Density was predicted solely from composition, whereas viscosity additionally considered temperature. To predict suitable glass leaching model parameters, a large simulated dataset was created by coupling MATLAB and the chemical reactive-transport code HYTEC, considering the state-of-the-art GRAAL model (glass reactivity in allowance of the alteration layer). The trained models were then subsequently applied to the large-scale industrial, experimental data to identify potentially appropriate model parameters. Results indicate that ensemble methods can accurately predict viscosity as a function of temperature and composition across all three industrial datasets. Glass density prediction shows reliable learning performance with predictions primarily being within the experimental uncertainty of the test data. Furthermore, machine learning can predict glass dissolution model parameters behavior, demonstrating potential value in GRAAL model development and in assessing suitable model parameters for large-scale industrial glass dissolution data.

Keywords: machine learning, predictive modelling, pattern recognition, radioactive waste glass

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Authors: Sánchez Acuña, Juan Camilo, Granados Gómez, Mildred Magaly, Navarrete Rodríguez, Luisa Fernanda

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Nowadays, the main biofuels source production as bioethanol is food crops. This means a high competition between foods and energy production. For this reason, it is necessary to take into account the use of new raw materials friendly to the environment. The main objective of this paper is to evaluate the potential of the agro-industrial banana crop residues in the production of bioethanol. A factorial design of 2⁴ was used, the design has variables such as pH, time and concentration of hydrolysis, another variable is the time of fermentation that is of 7 or 15 days. In the hydrolysis phase, the pH is acidic (H₂SO₄) or basic (NaOH), the time is 30 or 15 minutes and the concentration is 0.1 or 0.5 M. It was observed that basic media, low concentrations, fermentation, and higher pretreatment times produced better performance in terms of biofuel obtained.

Keywords: bioethanol, biofuels, banana waste, hydrolysis

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Authors: Vitool Suksankavanich

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This preliminary research aimed to explore the development of wastewater management of Bang Pu Sub- District Municipality, Samutprakan Province, in order to establish appropriate model for effective wastewater management that fit to the context of the area. The research posed three questions: [i] to what extent the promotion of social responsibility awareness built among the local community resulted in effectiveness of the local wastewater management; [ii] did the waste disposal management of Bang Pu Industrial Estate contribute to the overall environmental quality of Bang Pu Sub- District Municipality; and [iii] did the relationship between the community and the industrial factories have any effect on the wastewater management. The in- depth interview revealed main obstacles occurred in the process of wastewater management in the area. The fieldwork also contributed to a product of an appropriate model of effective wastewater management.

Keywords: legitimacy theory, stakeholder theory, social responsibility, wastewater management

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Authors: L. Al Ahmad, C. Latrille, D. Hainos, D. Blanc, M. Clausse

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A two-dimensional finite volume axisymmetric model is developed to predict the simultaneous heat and mass transfers during the drying of industrial sludge. The simulations were run using COMSOL-Multiphysics 3.5a. The input parameters of the numerical model were acquired from a preliminary experimental work. Results permit to establish correlations describing the evolution of the various parameters as a function of the drying temperature and the sludge water content. The selection and coupling of the equation are validated based on the drying kinetics acquired experimentally at a temperature range of 45-65 °C and absolute pressure range of 200-1000 mbar. The model, incorporating the heat and mass transfer mechanisms at different operating conditions, shows simulated values of temperature and water content. Simulated results are found concordant with the experimental values, only at the first and last drying stages where sludge shrinkage is insignificant. Simulated and experimental results show that sludge drying is favored at high temperatures and low pressure. As experimentally observed, the drying time is reduced by 68% for drying at 65 °C compared to 45 °C under 1 atm. At 65 °C, a 200-mbar absolute pressure vacuum leads to an additional reduction in drying time estimated by 61%. However, the drying rate is underestimated in the intermediate stage. This rate underestimation could be improved in the model by considering the shrinkage phenomena that occurs during sludge drying.

Keywords: industrial sludge drying, heat transfer, mass transfer, mathematical modelling

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Authors: N. Singh, A. Khullar, R. Shrivastava, I. Singh, A. S. Kumar

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Steel forms the basis of any modern society and is essential to economic growth. India’s annual crude steel production has seen a consistent increase over the past years and is poised to grow to 300 million tons per annum by 2030-31 from current level of 110-120 million tons per annum. Steel industry is highly capital-intensive industry and to remain competitive, it is imperative that it invests in operational excellence. Due to inherent nature of the industry, there is large amount of variability in its supply chain both internally and externally. Production and productivity of a steel plant is greatly affected by the bottlenecks present in material flow logistics. The internal logistics constituting of transport of liquid metal within a steel melting shop (SMS) presents an opportunity in increasing the throughput with marginal capital investment. The study was carried out at one of the SMS of an integrated steel plant located in the eastern part of India. The plant has three SMS’s and the study was carried out at one of them. The objective of this study was to identify means to optimize SMS hot metal logistics through application of industrial engineering techniques. The study also covered the identification of non-value-added activities and proposed methods to eliminate the delays and improve the throughput of the SMS.

Keywords: optimization, steel making, supply chain, throughput enhancement, workforce productivity

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Authors: Hyun-Woo Cho

Abstract:

Unexpected events may occur with serious impacts on industrial process. This work utilizes a data representation technique to model and to analyze process data pattern for the purpose of diagnosis. In this work, the use of triangular representation of process data is evaluated using simulation process. Furthermore, the effect of using different pre-treatment techniques based on such as linear or nonlinear reduced spaces was compared. This work extracted the fault pattern in the reduced space, not in the original data space. The results have shown that the non-linear technique based diagnosis method produced more reliable results and outperforms linear method.

Keywords: process monitoring, data analysis, pattern modeling, fault, nonlinear techniques

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Authors: M. Anji Reddy, R. Uma Devi

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Environmental planning for urban development is very much needed to reduce air pollution through the enhancement of vegetative cover in the cities like Hyderabad. This can be mainly based on the selection of appropriate native plant species as bioindicators to assess the impact of ambient Ozone. In the present study, tolerant species are suggested aimed to reduce the magnitude of ambient ozone concentrations which not only increase eco-friendly vegetation but also moderate air pollution. Hyderabad city is divided into 5 zones based on Land Use/Land Cover category further each zone divided into residential, traffic, industrial, and peri-urban areas. Highest ambient ozone levels are recorded in Industrial areas followed by traffic areas in the entire study area ( > 180 µg/m3). Biomonitoring of selected sixteen local urban plant species with the help of Air Pollution Tolerance Index (APTI) showed its susceptibility to air pollution. Statistical regression models in between the tolerant plant species and ambient ozone levels suggested five plant species namely Azardirachta indica A. Juss which have a high tolerant response to ambient ozone followed by Delonix regia Hook. along with Millingtonia hortensis L.f., Alestonia Scholaries L., and Samania saman Jacq. in the industrial and traffic areas of the study area to mitigate ambient Ozone pollution and also to improve urban greenery.

Keywords: air pollution tolerance index, bio-indicators, eco-friendly vegetation, urban greenery

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Authors: Dongwoo Kang, Yunsung Yoo, Injun Kim, Jongin Lee, Jinwon Park

Abstract:

Since industrial revolution, energy usage by human-beings has been drastically increased resulting in the enormous emissions of carbon dioxide into the atmosphere. High concentration of carbon dioxide is well recognized as the main reason for the climate change by breaking the heat equilibrium of the earth. In order to decrease the amount of carbon dioxide emission, lots of technologies have been developed. One of the methods is to capture carbon dioxide after combustion process using liquid type absorbents. However, for some nations, captured carbon dioxide cannot be treated and stored properly due to their geological structures. Also, captured carbon dioxide can be leaked out when crust activities are active. Hence, the method to convert carbon dioxide as stable and useful products were developed. It is usually called CCU, that is, Carbon Capture and Utilization. There are several ways to convert carbon dioxide into useful substances. For example, carbon dioxide can be converted and used as fuels such as diesel, plastics, and polymers. However, these types of technologies require lots of energy to make stable carbon dioxide into a reactive one. Hence, converting it into metal carbonates salts have been studied widely. When carbon dioxide is captured by alkanolamine-based liquid absorbents, it exists as ionic forms such as carbonate, carbamate, and bicarbonate. When adequate metal ions are added, metal carbonate salt can be produced by ionic reaction with fast reaction kinetics. However, finding metal sources can be one of the problems for this method to be commercialized. If natural resources such as calcium oxide were used to supply calcium ions, it is not thought to have the economic feasibility to use natural resources to treat carbon dioxide. In this research, high concentrated industrial wastewater produced from refined salt production facility have been used as metal supplying source, especially for calcium cations. To ensure purity of final products, calcium ions were selectively separated in the form of gypsum dihydrate. After that, carbon dioxide is captured using alkanolamine-based absorbents making carbon dioxide into reactive ionic form. And then, high purity calcium carbonate salt was produced. The existence of calcium carbonate was confirmed by X-Ray Diffraction (XRD) and Scanning Electron Microscopy (SEM) images. Also, carbon dioxide loading curves for absorption, conversion, and desorption were provided. Also, in order to investigate the possibility of the absorbent reuse, reabsorption experiments were performed either. Produced calcium carbonate as final products is seemed to have potential to be used in various industrial fields including cement and paper making industries and pharmaceutical engineering fields.

Keywords: alkanolamine, calcium carbonate, climate change, seawater, industrial wastewater

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Authors: Ankit Kamboj, Shikha Talwar, Nilesh Powar

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To successfully deliver our products in the market, the employees need to be in a safe environment, especially in an industrial and manufacturing environment. The consequences of delinquency in wearing safety glasses while working in industrial plants could be high risk to employees, hence the need to develop a real-time automatic detection system which detects the persons (violators) not wearing safety glasses. In this study a convolutional neural network (CNN) algorithm called faster region based CNN (Faster RCNN) with rotated bounding box has been used for detecting safety glasses on persons; the algorithm has an advantage of detecting safety glasses with different orientation angles on the persons. The proposed method of rotational bounding boxes with a convolutional neural network first detects a person from the images, and then the method detects whether the person is wearing safety glasses or not. The video data is captured at the entrance of restricted zones of the industrial environment (manufacturing plant), which is further converted into images at 2 frames per second. In the first step, the CNN with pre-trained weights on COCO dataset is used for person detection where the detections are cropped as images. Then the safety goggles are labelled on the cropped images using the image labelling tool called roLabelImg, which is used to annotate the ground truth values of rotated objects more accurately, and the annotations obtained are further modified to depict four coordinates of the rectangular bounding box. Next, the faster RCNN with rotated bounding box is used to detect safety goggles, which is then compared with traditional bounding box faster RCNN in terms of detection accuracy (average precision), which shows the effectiveness of the proposed method for detection of rotatory objects. The deep learning benchmarking is done on a Dell workstation with a 16GB Nvidia GPU.

Keywords: CNN, deep learning, faster RCNN, roLabelImg rotated bounding box, safety goggle detection

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Authors: Seon Tae Kim, Robert Hegner, Goksel Ozuylasi, Panagiotis Stathopoulos, Eberhard Nicke

Abstract:

High-temperature heat pumps (HTHP) that can supply heat at temperatures above 200°C can enhance the energy efficiency of industrial processes and reduce the CO₂ emissions connected with the heat supply of these processes. In the current work, the thermodynamic performance of 3 different vapor compression cycles, which use R-718 (water) as a working medium, have been evaluated by using a commercial process simulation tool (EBSILON Professional). All considered cycles use two-stage vapor compression with intercooling between stages. The main aim of the study is to compare different intercooling strategies and study possible heat recovery scenarios within the intercooling process. This comparison has been carried out by computing the coefficient of performance (COP), the heat supply temperature level, and the respective mass flow rate of water for all cycle architectures. With increasing temperature difference between the heat source and heat sink, ∆T, the COP values decreased as expected, and the highest COP value was found for the cycle configurations where both compressors have the same pressure ratio (PR). The investigation on the HTHP capacities with optimized PR and exergy analysis has also been carried out. The internal heat exchanger cycle with the inward direction of secondary flow (IHX-in) showed a higher temperature level and exergy efficiency compared to other cycles. Moreover, the available operating range was estimated by considering mechanical limitations.

Keywords: high temperature heat pump, industrial process, vapor compression cycle, R-718 (water), thermodynamic analysis

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Authors: Yu-Wen Chen, Szu-Wei Huang, Chung-Hsiang Mu, Kelvin Cheng

Abstract:

This paper developed a data-driven based model to deal with the causality between the Continuous Emission Monitoring System (CEMS, by Environmental Protection Administration, Taiwan) in industrial factories, and the air quality around environment. Compared to the heavy burden of traditional numerical models of regional weather and air pollution simulation, the lightweight burden of the proposed model can provide forecasting hourly with current observations of weather, air pollution and emissions from factories. The observation data are included wind speed, wind direction, relative humidity, temperature and others. The observations can be collected real time from Open APIs of civil IoT Taiwan, which are sourced from 439 weather stations, 10,193 qualitative air stations, 77 national quantitative stations and 140 CEMS quantitative industrial factories. This study completed a causal inference engine and gave an air pollution forecasting for the next 12 hours related to local industrial factories. The outcomes of the pollution forecasting are produced hourly with a grid resolution of 1km*1km on IIoTC (Industrial Internet of Things Cloud) and saved in netCDF4 format. The elaborated procedures to generate forecasts comprise data recalibrating, outlier elimination, Kriging Interpolation and particle tracking and random walk techniques for the mechanisms of diffusion and advection. The solution of these equations reveals the causality between factories emission and the associated air pollution. Further, with the aid of installed real-time flue emission (Total Suspension Emission, TSP) sensors and the mentioned forecasted air pollution map, this study also disclosed the converting mechanism between the TSP and PM2.5/PM10 for different region and industrial characteristics, according to the long-term data observation and calibration. These different time-series qualitative and quantitative data which successfully achieved a causal inference engine in cloud for factory management control in practicable. Once the forecasted air quality for a region is marked as harmful, the correlated factories are notified and asked to suppress its operation and reduces emission in advance.

Keywords: continuous emission monitoring system, total suspension particulates, causal inference, air pollution forecast, IoT

Procedia PDF Downloads 67