Operational optimization of copper flotation process based on the weighted Gaussian process regression and index-oriented adaptive differential evolution algorithm

Concentrate copper grade(CCG)is one of the important production indicators of copper flotation processes,and keeping the CCG at the set value is of great significance to the economic benefit of copper flotation industrial processes.This paper addresses the fluctuation problem of CCG through an operational optimization method.Firstly,a density-based affinity propagationalgorithm is proposed so that more ideal working condition categories can be obtained for the complex raw ore properties.Next,a Bayesian network(BN)is applied to explore the relationship between the operational variables and the CCG.Based on the analysis results of BN,a weighted Gaussian process regression model is constructed to predict the CCG that a higher prediction accuracy can be obtained.To ensure the predicted CCG is close to the set value with a smaller magnitude of the operation adjustments and a smaller uncertainty of the prediction results,an index-oriented adaptive differential evolution(IOADE)algorithm is proposed,and the convergence performance of IOADE is superior to the traditional differential evolution and adaptive differential evolution methods.Finally,the effectiveness and feasibility of the proposed methods are verified by the experiments on a copper flotation industrial process.

Automatic Synthesis of Batch Process Operating Procedures

A three-step synthesis strategy for the automatic synthesis of operating procedures in batch processoperations is presented in this paper.The first step is pre-operation which consists of a set of checks that mustbe considered before starting the basic process operation.The second step is operation which is described by a setof basic control instructions.The third step is post-operation described by a set of instructions that must becarried out when the basic process operation is terminated.The three-step synthesis method has been imple-mented as part of a prototype recipe management system.

Autonomous process collaboration framework for C4ISR system interoperation

Interoperability plays an important role in the joint command, control, communication, computer, intelligence, surveillance, reconnaissance(C4 ISR) operations. Coordinating and integrating operational processes to fulfill a common mission are challenged by the ever-changing battlefield and hence requires a cross-organizational process management that produces an autonomous, flexible and adaptable architecture for collaborative process evolution. The traditional business process collaboration pattern is based on the predefined "public-view" perspective and cannot meet the requirement of the joint task operations. This paper proposes a flexible visibility control mechanism and a dynamic collaboration framework for modeling and generating collaborative processes. The mechanism allows collaborators to define a set of visibility rules to generate different views of the private processes for different collaborations, which gives a great flexibility for the collaboration initiator to decide on an appropriate collaboration pattern. The framework supports collaborators to dynamically and recursively add a new process or even a new organization to an existing collaboration. Moreover, a formal representation of the processes and a set of generation algorithms are provided to consolidate the proposed theory.

Operation optimization of the steel manufacturing process: A brief review

Against the realistic background of excess production capacity, product structure imbalance, and high material and energy consumption in steel enterprises, the implementation of operation optimization for the steel manufacturing process is essential to reduce the production cost, increase the production or energy efficiency, and improve production management. In this study, the operation optimization problem of the steel manufacturing process, which needed to go through a complex production organization from customers' orders to workshop production, was analyzed. The existing research on the operation optimization techniques, including process simulation, production planning, production scheduling, interface scheduling, and scheduling of auxiliary equipment, was reviewed. The literature review reveals that, although considerable research has been conducted to optimize the operation of steel production, these techniques are usually independent and unsystematic.Therefore, the future work related to operation optimization of the steel manufacturing process based on the integration of multi technologies and the intersection of multi disciplines were summarized.

A Novel Close-loop Strategy for Integrating Process Operations of Fluidized Catalytic Cracking Unit with Production Planning Optimization

Production planning models generated by common modeling systems do not involve constraints for process operations, and a solution optimized by these models is called a quasi-optimal plan. The quasi-optimal plan cannot be executed in practice some time for no corresponding operating conditions. In order to determine a practi- cally feasible optimal plan and corresponding operating conditions of fluidized catalytic cracking unit （FCCU）, a novel close-loop integrated strategy, including determination of a quasi-optimal plan, search of operating conditions of FCCU and revision of the production planning model, was proposed in this article. In the strategy, a generalized genetic algorithm （GA） coupled with a sequential process simulator of FCCU was applied to search operating conditions implementing the quasi-optimal plan of FCCU and output the optimal individual in the GA search as a final genetic individual. When no corresponding operating conditions were found, the final genetic individual based correction （FGIC） method was presented to revise the production planning model, and then a new quasi-optimal production plan was determined. The above steps were repeated until a practically feasible optimal plan and corresponding operating conditions of FCCU were obtained. The close-loop integrated strategy was validated by two cases, and it was indicated that the strategy was efficient in determining a practically executed optimal plan and corresponding operating conditions of FCCU.

Quantitative evaluation of multi-process collaborative operation in steelmaking–continuous casting sections

The quantitative evaluation of multi-process collaborative operation is of great significance for the improvement of production planning and scheduling in steelmaking–continuous casting sections(SCCSs). However, this evaluation is difficult since it relies on an in-depth understanding of the operating mechanism of SCCSs, and few existing methods can be used to conduct the evaluation, due to the lack of full-scale consideration of the multiple factors related to the production operation. In this study, three quantitative models were developed, and the multiprocess collaborative operation level was evaluated through the laminar-flow operation degree, the process matching degree, and the scheduling strategy availability degree. Based on the evaluation models for the laminar-flow operation and process matching levels, this study investigated the production status of two steelmaking plants, plants A and B, based on actual production data. The average laminar-flow operation(process matching) degrees of SCCSs were obtained as 0.638(0.610) and 1.000(0.759) for plants A and B, respectively, for the period of April to July 2019. Then, a scheduling strategy based on the optimization of the furnace-caster coordinating mode was suggested for plant A. Simulation experiments showed higher availability than the greedy-based and manual strategies. After the proposed scheduling strategy was applied,the average process matching degree of the SCCS of plant A increased by 4.6% for the period of September to November 2019. The multi-process collaborative operation level was improved with fewer adjustments and interruptions in casting.

Application of Functional Operators with Shift to the Study of Renewable Systems When the Reproductive Process Is Described by Integrals with Degenerate Kernels

We continue studying systems whose state depends on time and whose resources are renewably based on functional operators with shift. In previous articles, we considered the term which described results of reproductive processes as a linear expression or as a shift summand. In this work, the reproductive term is represented using an integral with a degenerate kernel. A cyclic model of evolution of the system with a renewable resource is developed. We propose a method for solving the balance equation and we determine an equilibrium state of the system. Having applied this model, we can investigate problems of natural systems and their resource production.

A Knowledge Base System for Operation Optimization: Design and Implementation Practice for the Polyethylene Process

Setting up a knowledge base is a helpful way to optimize the operation of the polyethylene process by improving the performance and the ef ciency of reuse of information and knowledge two critical ele- ments in polyethylene smart manufacturing. In this paper, we propose an overall structure for a knowl- edge base based on practical customer demand and the mechanism of the polyethylene process. First, an ontology of the polyethylene process constructed using the seven-step method is introduced as a carrier for knowledge representation and sharing. Next, a prediction method is presented for the molecular weight distribution (MWD) based on a back propagation (BP) neural network model, by analyzing the relationships between the operating conditions and the parameters of the MWD. Based on this network, a differential evolution algorithm is introduced to optimize the operating conditions by tuning the MWD. Finally, utilizing a MySQL database and the Java programming language, a knowledge base system for the operation optimization of the polyethylene process based on a browser/server framework is realized.

Consequence Identification for Maloperation in Batch Process

Batch processes are important in chemical industry,in which operators usually play a major role and hazards may arise by their inadvertent acts.In this paper,based on hazard and operability study and concept of qualitative simulation,an automatic method for adverse consequence identification for potential maloperation is proposed.The qualitative model for production process is expressed by a novel directed graph.Possible operation deviations from normal operating procedure are identified systematically by using a group of guidewords.The proposed algorithm is used for qualitative simulation of batch processes to identify the effects of maloperations.The method is illustrated with a simple batch process and a batch reaction process.The results show that batch processes can be simulated qualitatively and hazards can be identified for operating procedures including maloperations.After analysis for possible plant maloperations,some measures can be taken to avoid maloperations or reduce losses resulted from maloperations.

Data-driven optimal operation of the industrial methanol to olefin process based on relevance vector machine

Methanol to olefin(MTO)technology provides the opportunity to produce olefins from nonpetroleum sources such as coal,biomass and natural gas.More than 20 commercial MTO plants have been put into operation.Till now,contributions on optimal operation of industrial MTO plants from a process systems engineering perspective are rare.Based on relevance vector machine(RVM),a data-driven framework for optimal operation of the industrial MTO process is established to fully utilize the plentiful industrial data sets.RVM correlates the yield distribution prediction of main products and the operation conditions.These correlations then serve as the constraints for the multi-objective optimization model to pursue the optimal operation of the plant.Nondominated sorting genetic algorithmⅡis used to solve the optimization problem.Comprehensive tests demonstrate that the ethylene yield is effectively improved based on the proposed framework.Since RVM does provide the distribution prediction instead of point estimation,the established model is expected to provide guidance for actual production operations under uncertainty.

A Multi-layer Information Integration Platform for Chemical Process Operation Systems

In the process industry, automation and process control systems are widely implemented, information integration is however far away from satisfactory. It remains a hard job for senior managers to make decisions based on the plant-wide real-time integrated information. This paper proposes a multi-layer information integration platform. In the data integration level, the standard for the exchange of product (STEP) and the extensible markup language (XML) are used to unify these data of the chemical process. In the model integration level, the models are integrated by using the neutral model repository and CAPE-OPEN. In the integration of process task, the common object request broker architecture (CORBA) is used as the communication mediator. The XML is taken as the data standard. A uniform information platform is thus constructed and realized. The proposed information integration platform is satisfactorily implemented to solve the Tennessee Eastman (TE) problem.

Thoughts on Transferring Traditional Operation to Full-process Logistic Service

通过阐述贵阳南站通过转变机制、拓展运输市场，站专一体、打造专业化市场，主动营销、创建全程运输品牌，无缝衔接、助力“前店后厂”装运等向全程物流服务转变的主要做法，在分析实践中存在“三个明显”和“三个不足”的基础上，提出组建自营车队，掌握市场主动权；优化价格机制，适应市场需求；依托改貌基地，努力建好物流港；提升硬件水平，增强货场能力等进一步向全程物流服务转变的措施。

Controlling of crustacean zooplankton reproduction in biological activated carbon (BAC) filters by strengthen operation and management of conventional process

To counter the mass reproduction and penetration of crustacean zooplankton in Biological Activated Carbon(BAC)filters which may result in the presence of organisms in potable water and water pollution,this paper analyzed the factors affecting organisms' reproduction in BAC filters.A comparative study was performed on the density and composition of crustacean zooplankton of the concerned water treatment units of two advanced water plants(Plant A and B)which with the same raw water and the same treatment technique in southern China.The results obtained show that the crustaceans' density and composition was very different between the sand filtered water of Plant A and Plant B.which Harpacticoida bred sharply in the sediment tanks and penetrated sand filter into BAC filters was the primary reason of crustaceans reproduce in BAC filters of Plant A.For prevention of the organisms reproduction in BAC,some strengthen measures was taken including pre-chlorination,cleaning coagulation tanks and sediment tanks completely,increasing sludge disposal frequency to stop organisms enter BAC filters,and the finished water quality was improved and enhanced.

Some Results about the Sample Path Properties of Markov Processes with Independent Self-Similar Components

This paper considers a special class of operator self-similar processes Markov processes {X（t）, t≥0} with independent self-similar components, that is, X （ t ） =（X^1（t）,…,X^d（t））, where {X^i（t）,t≥0}, i=1,2,…,d are d independent real valued self-similar Markov processes. By means of Brel-Cantelli lemma, we give two results about asymptotic property as t→∞ of sample paths for two special classes of Markov processes with independent self-similar components.

Operational Performance Evaluation of Corn Processing Industry Technological Innovation Alliance Based on Survey Data in Heilongjiang Province

This paper selected the corn processing industry technology innovation alliance in Heilongjiang Province as the research object, evaluated the operational performance of the alliance by using analytic hierarchy process(AHP) and fuzzy comprehensive evaluation methods. AHP empirical results showed that the satisfaction of information communication and the satisfaction of the management process were the weakest. And the order from high to low on the level of indicators of the impact for the alliance was the result of alliance operations and the process of alliance operations, the behavioral attitude of alliance members. Besides, the results of fuzzy comprehensive evaluation showed that the operational performance of the corn processing industry technology innovation alliance in Heilongjiang Province was in the general level.

FTC of hidden Markov process with application to resource allocation in air operation

This paper investigates the feedback control of hidden Markov process（HMP） in the face of loss of some observation processes.The control action facilitates or impedes some particular transitions from an inferred current state in the attempt to maximize the probability that the HMP is driven to a desirable absorbing state.This control problem is motivated by the need for judicious resource allocation to win an air operation involving two opposing forces.The effectiveness of a receding horizon control scheme based on the inferred discrete state is examined.Tolerance to loss of sensors that help determine the state of the air operation is achieved through a decentralized scheme that estimates a continuous state from measurements of linear models with additive noise.The discrete state of the HMP is identified using three well-known detection schemes.The sub-optimal control policy based on the detected state is implemented on-line in a closed-loop,where the air operation is simulated as a stochastic process with SimEvents,and the measurement process is simulated for a range of single sensor loss rates.

Study on Winter Operation Process of the Surface Flow Constructed Wetland in Tianjin Area

[Objective] The research aimed to study winter operation process of the surface flow constructed wetland in ＂rianjin area. [Method] In view of climate characteristics in Tianjin, by the way of running under the ice, winter operation experiment of the surface flow constructed wetland in Tianjin was conducted, with the expectation to get some useful process parameters to run such systems in North China in winter. [ Result] Although purification effect of the sewage by surface flow constructed wetland in winter was worse than that in other seasons （ average reduction of about 20%）, surface flow constructed wetland running under the ice was feasible in Tianjin area. When surface flow constructed wetland in North China ran under ice in winter, it was suggested that the outlet must be located in a low position to prevent to be completely frozen, and running water depth should not be less than 50 -60 cm. The hydraulic load could be raised on the basis of reflux, and hydraulic retention time should maintain less than 4 d to keep water-soil interface not freezing. Inlet water depth should be increased as much as possible to improve temperature in the system. V Conclusion1 The research could provide reference for promotion and application of the surface flow constructed wetland in North China.

Low-Power Operational Amplifier for Real-Time Signal Processing System of Micro Air Vehicle

A low-power complementary metal oxide semiconductor（CMOS） operational amplifier （op-amp） for real-time signal processing of micro air vehicle （MAV） is designed in this paper.Traditional folded cascode architecture with positive channel metal oxide semiconductor（PMOS） differential input transistors and sub-threshold technology are applied under the low supply voltage.Simulation results show that this amplifier has significantly low power,while maintaining almost the same gain,bandwidth and other key performances.The power required is only 0.12 mW,which is applicable to low-power and low-voltage real-time signal acquisition and processing system.

Recurrent Autoencoder Ensembles for Brake Operating Unit Anomaly Detection on Metro Vehicles

The anomaly detection of the brake operating unit (BOU) in thebrake systems on metro vehicle is critical for the safety and reliability ofthe trains. On the other hand, current periodic inspection and maintenanceare unable to detect anomalies in an early stage. Also, building an accurateand stable system for detecting anomalies is extremely difficult. Therefore,we present an efficient model that use an ensemble of recurrent autoencodersto accurately detect the BOU abnormalities of metro trains. This is the firstproposal to employ an ensemble deep learning technique to detect BOUabnormalities in metro train braking systems. One of the anomalous caseson metro vehicles is the case when the air cylinder (AC) pressures are less thanthe brake cylinder (BC) pressures in certain parts where the brake pressuresincrease before coming to a halt. Hence, in this work, we first extract the dataof BC and AC pressures. Then, the extracted data of BC and AC pressuresare divided into multiple subsequences that are used as an input for bothbi-directional long short-term memory (biLSTM) and bi-directional gatedrecurrent unit (biGRU) autoencoders. The biLSTM and biGRU autoencodersare trained using training dataset that only contains normal subsequences. Fordetecting abnormalities from test dataset which consists of abnormal subsequences, the mean absolute errors (MAEs) between original subsequences andreconstructed subsequences from both biLSTM and biGRU autoencoders arecalculated. As an ensemble step, the total error is calculated by averaging twoMAEs from biLSTM and biGRU autoencoders. The subsequence with totalerror greater than a pre-defined threshold value is considered an abnormality.We carried out the experiments using the BOU dataset on metro vehiclesin South Korea. Experimental results demonstrate that the ensemble modelshows better performance than other autoencoder-based models, which showsthe effectiveness of our ensemble model for detecting BOU anomalies onmetro trains.

Impact of Operational Process Factors on Strategy Implementation in Microfinance Organisations in a Developing Country

This paper sets to explore management perceptions regarding the impact of operational process factors on strategy implementation in microfinance organisations in Kenya.Small and medium enterprises(SMEs)play a critical role in developing countries as a source of employment creation and a basis for industrialization.However,the sector receives inadequate financial support from commercial banks as it is considered to bear high risks and operational costs associate with lending small loan amounts.Microfinance organisations(MFOs)that serve this sector will need to expand their operations to increase their outreach to SMEs.Formulation and implementation of competitive strategies will enable MFOs to achieve growth and sustainability.Content,context and operational process factors appear to have a significance positive relationship to the level of strategy implementation.This paper is focusing on operational process factors impacting on strategy implementation and is part of a full study on the topic of strategy implementation in MFOs.Comprehensive literature review provided the theoretical framework for the study.Primary data were collected by means of a survey obtaining 300 self-administered questionnaires from managers in 135 MFOs in Kenya.The study revealed that the level of strategy implementation in MFOs in Kenya is moderate to high.This study has revealed that the operational process category of factors is more significant to the level of strategy implementation than content and context factors.Five operational process factors critical to strategy implementation include:operational planning and monitoring,management control systems,people-strategy fit,teamwork,and effective communication.Further,the level of strategy implementation has significance positive influence to MFOs’financial sustainability and outreach.Practical guidelines are provided to assist MFOs in developing countries to improve the level of strategy implementation by focusing on operational process factors.