Improvement Of Industrial Processes Research Articles

Deep Learning Approach for Industrial Process Improvement

The full operation of an industrial processing facility with artificial intelligence has been the holy grail of Industry 4.0. One of the inherent difficulties is the enumerate and complex nature of processing information within an industrial plant. Hence, such data should be processed efficiently. This paper demonstrates the effectiveness of a deep auto-encoder neural network for the dimensionality reduction of industrial processing data. The deep auto-encoder neural network functions to intake all possible processing data from the processing system by sending it into an encoder neural network. Subsequently, the encoder condenses the data into highly compressed encoded variables. The network is trained in an unsupervised manner, where a decoder neural network simultaneously attempts to revert the encoded variables to their original form. Such a deep learning approach allows data to be highly compressed into lower dimensions. The coded variables retain critical information of the processing system, allowing reconstruction of the full process data. Auto-encoder neural networks are also able to provide noise removal for encoded data. For application, the encoded variable can be utilized as an effective dimension-reduced variable that can be used for plant-wide optimization. This paper also discusses the further applications of encoded variables for industrial process improvements using the Industrial Internet of Things (IIoT) technologies.

Electrochemical Direct Partial Oxidation of Methane to Methanol

Joonbaek Jang received his B.S. from Korea University in 2016. He then moved to the University of Pennsylvania where he obtained his M.S. working with Prof. Raymond J. Gorte. During his master’s degree, Joonbaek used atomic layer deposition to modify metal oxide catalysts for the improvement of industrial catalytic processes. In 2018, he joined the Morales-Guio Lab in the Department of Chemical and Biomolecular Engineering at UCLA. Joonbaek is currently working toward the understanding of electrode/electrolyte interfaces and mass transport effects in electrocatalytic processes for sustainable energy applications. Kangze Shen received his B.S. in Materials Chemistry from University of Science and Technology of China in 2018. His undergraduate research with Prof. Yitai Qian focused on the development of high-performance electrode materials for rechargeable Li-ion and Na-ion batteries. He then joined the Morales-Guio Lab in the Department of Chemical and Biomolecular Engineering at UCLA where he is working toward the understanding of electrocatalytic processes and electrochemical systems engineering in sustainable energy applications. Carlos G. Morales-Guio is an Assistant Professor of Chemical and Biomolecular Engineering at UCLA. The Morales-Guio Lab is interested in electrochemical catalysis, particularly with respect to energy and chemical transformations for sustainable energy applications. The lab is currently focused on understanding fundamentals of mass and charge transport coupled to electrochemical transformations that will guide the scale up of electrocatalytic reactors. Carlos received his B. Eng. degree from Osaka University in 2011 and his M.S. and Ph.D. in Chemistry and Chemical Engineering from EPFL in 2013 and 2016, respectively. Most recently, he was a postdoctoral research fellow at Stanford University before joining UCLA in 2018.

Environmental problems caused by the activities of oil and gas companies and actions to reduce environmental harm

The purpose of this study is to analyze the environmental problems caused by the activities of the oil and gas sector. The problem of the study is the most significant, as Russia is a major state for the production and processing of oil and gas products, so many regions face serious environmental problems. The objectives of the study – to reveal the environmental problems in the activities of oil and gas companies in Russia, to analyze the environmental rating of oil and gas companies in Russia. The author also presents an analysis of the activities of the oil and gas sector to date. It has a huge impact on the environment of many countries. There are serious environmental problems that harm the life of all living beings of the planet. It is concluded that oil and gas companies have realized the importance of existing problems and pursues the goal of its improvement, improvement of industrial processes to eliminate environmental damage. Indicative in our country is the environmental rating of oil and gas companies, where the leading position is occupied by companies pursuing sustainable development and caring for the environment, which certainly affects their reputation. In addition, the article provides an example of the actions of LUKOIL – recognized in 2018 as the most open company that publishes all information on environmental safety.

The intensity of private funding and the results of university? Firm interactions: the case of Brazil

Purpose The purpose of this paper is to investigate the academic side of university–firm linkages, reporting the results of research (called the “BR Survey”, a primary database) conducted in Brazil with leaders of research groups that interacted with firms. The authors analysed the answers from 662 research groups (from both universities and research institutes) to investigate whether the intensity of private funds affects the results of the interactions. The main intent is to answer the following question: Is there a difference between funding sources and the type of results achieved by research groups when interacting with firms? Design/methodology/approach To verify the impact of some variables on the perception of the main results of university–firm interactions, highlighting the impact of funding sources, the authors present a Logit Model defined with binary dependent variables. The null value is categorized as a “scientific result” (new scientific discoveries and research projects; publications, theses and dissertations; human resources’ and students’ education) and the value 1 is classified as an “innovative/technological result” (new products, artefacts and processes; improvement of industrial products and processes; patents, software, design and spin-off firms). Findings The authors found that the modes of interaction (relationship types) and some knowledge transfer channels, besides the number of interactions with firms, have statistically significant coefficients, so their values present different impacts on the results of the interaction. The results suggest that the Brazilian innovation policy towards a more active and entrepreneurial role of universities is fostering innovative/technological results from university–firm interactions. Originality/value The originality of the study lies on the results found that given the fact that private funding sources do not affect the conventional mission of Brazilian universities – teaching and research – university research groups should be even more incentivized to search for private funds to carry out their research. This may be a solution to the public fund scarcity and may help in reducing the historical distance between universities and firms in Brazil.

Direct Contact Condensation Jet in Cross-Flow Using Computational Fluid Dynamics

The computational fluid dynamics is an important methodology to study the characteristics of flows in nature and in a number of engineering applications. Modeling nonisothermal flows may be useful to predict the main flow behavior allowing the improvement of equipment and industrial processes. In addition, investigations using computational models may provide key information about the fundamental characteristics of flow, developing theoretical groundwork of physical processes. In the last years, the topic of phase change has been intensively studied using computational fluid dynamics due to the computational and numerical advances reported in the literature. Among several issues related to the phase change topic, direct contact condensation (DCC) is widely studied in the literature since it is part of a number of industrial applications. In the present work, DCC was studied using a mathematical and computational model with an Eulerian approach. The homemade code MFSim was used to run all the computational simulations in the cluster of the Fluid Mechanics Laboratory from the Federal University of Uberlandia (UFU). The computational model was validated and showed results with high accuracy and low differences compared to previous works in the literature. A complex case study of DCC with cross-flow was then studied and the computational model provided accurate results compared to experimental data from the literature. The jet centerline was well represented and the interface dynamic was accurately captured during all the simulation time. The investigation of the velocity field provided information about the deeply transient characteristic of this flow. The v-velocity component presented the more large variations in time since the standard deviation was subjected to a variation of about 45% compared to the temporal average. In addition, the time history of the maximum resultant velocities observed presented magnitude from 29 m/s to 73 m/s. The importance of modeling three-dimensional (3D) effects was confirmed with the relevance of the velocity magnitudes in the third axis component. Therefore, the Eulerian phase change model used in the present study indicated the possibility to model even complex phenomena using an Eulerian approach.

Public Infrastructure Project Tendering Through Public Private Partnerships (PPP) – A Literature Review

Public Private Partnerships (PPP) in Malaysia have been inundated by various controversies and criticisms from the very beginning. Many of the constraints that occur in PPP projects is due to the failure in tendering stage. Bidding or tender for a PPP project is usually much more complex than a traditional public-sector project involving the appointment of top advisers and designers at a great fee in the preparation of detailed design, comprehensive planning, extensive bid documentation, and lengthy clarifications. These problems as being the reason behind several high-profile withdrawals during the early PPP tenders, resulting in some preferred bidders being selected by defaults as other competitors withdrew. Base on the above premise, this study attempts to propose PPP tendering process improvement in Malaysian construction industry. This paper aims at providing an overview about literature on tendering process in PPP/PFI. The objectives of the research are to identify and understand the PPP implementation practices in Malaysia; to determine issues and challenges in PPP tendering stage; and to propose PPP tendering improvement. The approach is based on the analysis of the pertinent publications on the theme. Three main interest areas can be found in the literature which is; tendering procedure, issues and challenges, and strategies that could be enhance PPP tendering process in the Malaysian construction industry.

Enhancing stock efficiency and environmental sustainability goals in direct distribution logistic networks

In modern business, industrial companies embrace lean philosophy to increase their efficiency moving toward the so-called continuous improvement of industrial processes. In parallel, according to the international regulations and stakeholder pressures, rising attention is toward sustainable environmental, i.e., green, practices. A relevant scientific area addresses the topic of matching lean management (LM) and green management (GM) principles within logistics, from a quantitative and optimised perspective. This paper follows this stream and proposes a bi-objective model optimising stock efficiency and environmental sustainability in the design of direct distribution logistic networks. The former goal belongs to LM, the latter belongs to GM. The model application to an Italian case study showcases its benefit reducing the average stock without a relevant increase of the emissions due to frequent replenishments. A cost analysis of the results completes this paper to include the economic dimension within the study boundaries.

Enhancing stock efficiency and environmental sustainability goals in direct distribution logistic networks

In modern business, industrial companies embrace lean philosophy to increase their efficiency moving toward the so-called continuous improvement of industrial processes. In parallel, according to the international regulations and stakeholder pressures, rising attention is toward sustainable environmental, i.e., green, practices. A relevant scientific area addresses the topic of matching lean management (LM) and green management (GM) principles within logistics, from a quantitative and optimised perspective. This paper follows this stream and proposes a bi-objective model optimising stock efficiency and environmental sustainability in the design of direct distribution logistic networks. The former goal belongs to LM, the latter belongs to GM. The model application to an Italian case study showcases its benefit reducing the average stock without a relevant increase of the emissions due to frequent replenishments. A cost analysis of the results completes this paper to include the economic dimension within the study boundaries.

Kanban system based on manufacturing equipment operation monitoring

This work paper presents a single-channel Kanban solution where ticketing from downstream operator to the upstream operator in production flow is automatically performed when the completion of operations is identified. Thus, a more efficient transmission and placement mechanism for the tickets is provided for real-time operation of the machines, compared with others Kanban solutions. Our proposed solution contains elements of modern interdisciplinary research: industrial process improvement solutions using one Just in Time methodology: Kanban system, self – harvesting sensors, non-invasive monitoring solutions, multiple-source acquisition software, complex event processing and real-time parallel processing, use of Machine Learning analysis techniques (Deep Learning networks) to identify equipment operating regimes, use of ad hoc radio networks for data communication. The system was developed at an experimental model level. The article presents, with results, a case study in which we have two operators in a production stream. As will be shown, the system has a high degree of scalability, so it can easily be extended to any number of operators in the production stream.

EL CENTRO DE FABRICACIÓN AVANZADA AERONÁUTICA, DEL PROYECTO A LA REALIDAD

Located in the Technological Park of Bizkaia, it was inaugurated on 15 November and is a leading centre of aeronautical manufacturing, with international projection and focused on the improvement of industrial processes and advanced machinery.

SPATIAL MODELING OF TRANSPORT DEVELOPMENT OF FOREST AREA AND THEIR POTENTIAL ENVIRONMENTAL RISKS

Permanentattributesoftimberharvestingareanumberofpotentialenvironmentalrisks, eachofwhichcancausesignificantdamagetotheenvironment. The intensive development of technology and the improvement of industrial production processes have led to a significant increase in technogenic impact both on increasing catastrophic natural disasters and on the global climate change formation. The adoption of the World Environmental Constitution by all the states would be an effective means of regulating and minimizing these negative processes. Timber harvesting is one of the most dangerous types of technogenic impact on the forest environment, as the forest stand, young growth, natural watercourses and soil are damaged during logging and transportation. However, the degree of the negative impact of timber harvesting can be reduced to an ecologically acceptable level, and technical indicators of the use of timber-hauling machinery can be brought to economically feasible values by properly assessing the intensity of the environmental risk of taking a decision on certain technical and technological issues and the implementation of environmental management of this process. The article presents some approaches to the creation of GIS spatial planning model of transport development of forest-exploitation area based on the cost estimation of timber skidding considering technogenic impact of forest machines. The development of the model of forest transportation planning is a complex task. In order to solve this task, the system under investigation should be divided into separate interconnected modules, each acting as its own model: the models for forest transportation planning, the database, formulation of the task, the results of modeling, an analysis of transport movement possibilities, an analysis of environmental damage, the assessment and improvement of the existing forest road network. Concerning the proposed model and methodology that is based on the analysis of potential environmental risks associated with the rutting and cost-assessment of timber skidding, we have obtained the model map of environmentally-acceptable types of timber-hauling machines for a real forest exploitation area, the Rozhanka forest district, the Slavsk State Forestry Enterprise in particular. The proposed model makes it possible to substantiate environmentally safe and economically feasible ways of skidding, estimate the ratio of transport development of a forest area using various terrestrial technical means (wheeled and crawler tractors or cable systems), as well as to outline the possible occurrence, intensity and spread of environmental hazards associated with timber harvesting.

Chilled Ammonia Process Scale-up and Lessons Learned

The GE Chilled Ammonia Process (CAP) is a post combustion CO2 capture technology that produces a high purity CO2 product stream that can be utilized in the existing and new markets. The development of the CAP technology began with laboratory bench-scale experiments to confirm that aqueous ammonia solution effectively absorbs CO2 with sufficiently low vapor phase ammonia emissions at reduced temperatures. From these results, a technology development program was initiated to scale-up and validate the process for commercialization.The approach taken here is illustrative of industrial scale process development and improvement. For the CAP CO2 capture technology, the development effort involved an iterative approach as information from the different development stages was obtained to set environmental & economic targets, develop predictive tools and models for process optimization, and to support validation efforts at operating facilities. Over the course of the program, the technology was successfully tested on flue gasses produced from coal, oil, and natural gas combustion, in addition to flue gas produced from refinery applications. Process know-how and operational experience was gained and together with validated data from bench-scale and pilot plant facilities was returned to push process design improvement and the development of predictive models. Currently, the CAP design is also modified and extended into applications involving Urea, Methanol, and Soda Ash Production.While many lessons learned and process improvement opportunities have been extracted from pilot plant and other test facilities, pilot plant results and process modeling studies are still unveiling potential for further improvement. Optimization and integration with the power generation facility occurred in the development phases of several FEED studies for large CCS plants. The CAP design is ready for a demonstration-scale project and now is much improved from the design that was tested originally at laboratory bench-scale. For example, the CAP scrubbing solution is now operated in a non-solids mode where precipitation is not a part of the overall operational strategy and the process flow scheme is now modified and improved from original flow schemes implemented at early pilot facilities to improve performance at reduced cost.This work summarizes the bench-scale, pilot-scale, and validation facility results and offers insights into the lessons learned and effort required bringing the technology into commercialization at an industrial scale. The lessons learned from each of the pilot plants at different sizes are illustrated and the associated impact of the results from each pilot plant in the current CAP product offering is also discussed. A summary of the important results from CAP test facilities including Stanford Research International (SRI), WE energies, EONCAP-Karlshamm, AEP Mountaineer, TCM and GE's pilot facility in Vaxjo, Sweden are presented. Distinguishing features of the GE CAP are provided drawing comparison to open literature versions of ammonia based CO2 capture processes. Evolution of key performance parameters such as energy demand, product quality, solvent strength, process flow scheme, etc., at the different plant sizes are also discussed. In addition, the current state of development for extending the technology into areas where CO2 may be utilized productively are also be addressed in addition to the latest improvement concepts currently being studied on CAP. Finally, the paper will also summarize the advantages of CAP as compared to conventional amine based processes.

A Cross-Strait Comparison of Innovation Policy under Industry 4.0 and Sustainability Development Transition

While the advent of Industry 4.0 is emblematic of national strategy for industrial revitalization, the proliferation of technology has drastically changed the landscape of many major sectors of global industries. Industry 4.0 encompasses multi-dimensional concepts—including computerization, digitization, and intelligentization—of business operations based on cyber-physical-systems (CPS) and the Internet-of-Things (IoTs). The vision of Industry 4.0 will bring about improvements in industrial processes, ranging from engineering, material usage, supply chains, and product lifecycle management, to the horizontal value chain. This research project adopts a descriptive analysis with descriptive statistics under the innovation policy framework proposed by Rothwell and Zegveld. This report also informs a comparative policy analysis across China and Taiwan. From the perspectives of industry coalition and competition, this cross-strait comparison lends itself to being a policy-making reference. Results reveal that China, in terms of policy-making, concentrates on ‘political’ and ‘legal/regulatory’ aspects of environmental policy, as well as the theme of ‘public service’ of the demand-side policy. Taiwan also emphasizes the ‘environmental-side’ policy like China, whereas Taiwan focuses more on ‘education/training’ of the supply-side policy.

The Capability Maturity Model as an Industrial Process Improvement Model

This study examined the potential of adapting the software Capability Maturity Model as a process improvement paradigm within the context of industrial process improvement. Traditional methods of process improvement incorporate some facets of Total Quality Management (TQM), business process improvement (BPI), business process reengineering (BPR), business process management (BPM), benchmarking, regulation, legislation, Six Sigma, and standards. Hypothesis testing showed two statistically significant outcomes regarding the first and the fifth maturity levels reflecting ad hoc processes and optimized processes, respectively.

ChemInform Abstract: Kinetics and Mechanism of Catalytic Carbon Gasification

AbstractReview: 105 refs.

A conceptual hybrid framework for industrial process improvement: integrating Taguchi methods, Shainin System and Six Sigma

Design of Experiments (DoE) has evolved as powerful industrial statistics tool for managing and improving processes in diverse industries. The three broad approaches of DoE in practice: classical or traditional methods, Taguchi methods and Shainin System (SS), have their merits and demerits for a extensive industrial experimentation. Nonetheless, the power of these DoE approach is not fully harnessed in established process improvement frameworks in industries. On the other side, Six Sigma DMAIC is a well-accepted methodology for improving process capability through focus on customer’s requirement (CTQ). The use of DoE in traditional DMAIC framework is limited to quantification of influence factors on CTQ. To offer a contribution to this paucity, this paper proposed a conceptual Six Sigma/DOE hybrid framework aiming to integrate SS, Taguchi methods and Six Sigma DMAIC for process improvement in complex industry environment. A case on improving DF generation process in shock absorber assembly was developed to validate the effectiveness of the framework for intricate problem-solving.

Raptor’s “Right Hunger” Characterization to Develop Sustainable Exclusion Areas for wildlife at Civil & Military Airports

Abstract The bird strike damage on aircrafts is a widely studied matter [1] with a high economic impact on stakeholders finances. Some authors estimate it in about USD1.2 Billion for nowadays commercial worldwide activity [2], and more than USD937 million in direct and other monetary losses per year just for the United States, as an example of civil aviation industry [3]. The present techniques to face this problem have been previously analyzed in order to decrease the wild life hazards at the airport facilities [4] however nowadays there is a new point of view to prevent this risk at airports that requires an interesting approach in relationship with industrial process improvement examples, such approach lies on preserving the natural life at the airport facilities by developing raptor micro-habitats than change into exclusion areas when the risk of being hunted is recognized by the existing wildlife. Therefore, the main goal of this paper is to share several experiences developed at the Spanish dual airport (military & civilian) of San Javier (Spain), as a case of study in where the mathematics and nonlinear sciences provides the foundations of the ontological knowledge for falconry performance as a Wildlife Control Technique for airport facilities.

The effect of radiative heat transfer characteristics on vacuum directional solidification process of multicrystalline silicon in the vertical Bridgman system

In the vertical Bridgman system for multicrystalline silicon vacuum directional solidification process, the radiation heat transfer characteristics have a significant impact on the quality of crystal growth. In this paper, the effect of heat transfer characteristics under different pulling-down rates on the vacuum directional solidification process was investigated. Simplified radiation view factor dependent on pulling-down rate in pilot-scale vertical Bridgman system was derived. Combined with the transient simulation results, we obtained the heat transfer characteristics inside the furnace, and proposed the optimization scheme by using a rate of slowly first and then faster to pull down the crucible, which can not only satisfy thermal conditions of crystal growth, but also shorten the solidification time and effectively reduce the energy consumption. In addition, according to the characteristics of the radiative heat transfer under vacuum condition and the change of view factor, it was found that an improved design by widening the cold zone of the furnace can narrow the temperature gradient in the silicon ingot, and greatly decrease the thermal stresses, which in turn can aid in the design of future industrial equipment and process improvements.

Transcriptomic response of Saccharomyces cerevisiae for its adaptation to sulphuric acid-induced stress.

In bioethanol production plants, yeast cells are generally recycled between fermentation batches by using a treatment with sulphuric acid at a pH ranging from 2.0 to 2.5. We have previously shown that Saccharomyces cerevisiae cells exposed to sulphuric acid treatment induce the general stress response pathway, fail to activate the protein kinase A signalling cascade and requires the mechanisms of cell wall integrity and high osmolarity glycerol pathways in order to survive in this stressful condition. In the present work, we used transcriptome-wide analysis as well as physiological assays to identify the transient metabolic responses of S. cerevisiae under sulphuric acid treatment. The results presented herein indicate that survival depends on a metabolic reprogramming of the yeast cells in order to assure the yeast cell viability by preventing cell growth under this harmful condition. It involves the differential expression of a subset of genes related to cell wall composition and integrity, oxidation-reduction processes, carbohydrate metabolism, ATP synthesis and iron uptake. These results open prospects for application of this knowledge in the improvement of industrial processes based on metabolic engineering to select yeasts resistant to acid treatment.

Statistical Process Control for Process Improvement in Industry: A Case Study

Statistical Process Control for Process Improvement in Industry: A Case Study