Process Monitoring System Research Articles

A novel Q-based online model updating strategy and its application in statistical process control for rubber mixing

To overcome the large time-delay in measuring the hardness of mixed rubber, rheological parameters were used to predict the hardness. A novel Q-based model updating strategy was proposed as a universal platform to track time-varying properties. Using a few selected support samples to update the model, the strategy could dramatically save the storage cost and overcome the adverse influence of low signal-to-noise ratio samples. Moreover, it could be applied to any statistical process monitoring system without drastic changes to them, which is practical for industrial practices. As examples, the Q-based strategy was integrated with three popular algorithms (partial least squares (PLS), recursive PLS (RPLS), and kernel PLS (KPLS)) to form novel regression ones, QPLS, QRPLS and QKPLS, respectively. The applications for predicting mixed rubber hardness on a large-scale tire plant in east China prove the theoretical considerations.

Self-adjusting Process Monitoring System in Series Production

Modern monitoring systems in machine tools are able to detect process errors promptly. Still, the application of monitoring systems is restricted by the complexity of parameterization for save monitoring. In most cases, only specially trained personnel can handle this job especially for multi-purpose machines. The aim of the research project “Proceed” is to figure out in which extent a self-parameterization and autonomous optimization of monitoring systems in industrial series production can be realized. Therefore, a self-adjusting and self-tuning process monitoring system for series production has been developed. This system is based on multi-criteria sensor signal evaluation and is able to assess its monitoring quality quantitatively. For this purpose, the complete process chain of parameterization has been automated. For series production it is assumed, that the first process is not defective. So, process sensitive features are identified by a correlation analysis with a reference signal. The reference signal is selected through an analysis of the process state by an expert system. To assess the monitoring quality resulting from automatic parameterization, normed specific values were used. These values describe the monitoring quality with the help of the distance between a feature and its threshold normed to signal amplitude and noise. A second indicator is the reaction of the monitoring system to a synthetic error added to signal a sequence. Thus it is possible to estimate monitoring quality corresponding to automatic parameterization. The validation is carried out by a comparison between the result of the assessment and the reaction ability of the monitoring system to real process errors from milling, drilling and turning processes.

Perspectives on Process Monitoring of Industrial Systems

Process monitoring systems are necessary for ensuring the long-term reliability of the operation of industrial systems. This article provides some perspectives on progress in the design of process monitoring systems over the last twenty years. Different techniques that can be applied for fault detection, fault identification, and fault diagnosis are summarized. The challenges in the field and opportunities for future research are discussed. When looking into the future, it is argued that advances are likely to come from combining different methods to exploit the strengths of various techniques while minimizing their weaknesses.

Tool State Assessment for Reduction of Life Cycle Environmental Impacts of Aluminium Machining Processes via Infrared Temperature Monitoring

Modern industrial machining environments face new challenges in implementing process monitoring systems to improve energy efficiency whilst ensuring quality standards. A process monitoring methodology for tool state identification during milling of aluminium has been implemented through the utilisation of an infrared (IR) camera. A features extraction procedure, based on statistical parameters calculation, was applied to temperature data generated by the IR camera. The features were utilised to build a fuzzy c-means (FCM) based decision making support system utilising pattern recognition for tool state identification. The environmental benefits deriving from the application of the developed monitoring system, are discussed in terms of prevention of rework/rejected products and associated energy and material efficiency improvements.

ICA-Multiclass SVM as a Monitoring System of Complex Processes

Nowadays due to advancement of technology, the processes have become increasingly complex. So perform eectively monitor and correct diagnosis of these, has become a challenging task. this because the current processes have in common presence of combinations and correlation between analog and digital variables, presence of noise, etc. This issued is overcome by multivariate statistical methods which can eciently represent the dierent correlations between variables. One of the most popular methods for process monitoring is the Hotelling's T 2 distance but a large amount of data makes the process monitoring a dicult task. Principal Component Analysis (PCA) is used for the data reduction which means the extraction of few numbers representing the most variance of the analyzed data. However the use of these two methods is limited to normal multivariate data set and in industry rarely normal data set is presented, hence dierent methods are used for this purpose. Independent component analysis (ICA) has been used in no-normal mul- tivariate processes. In this paper a monitoring and fault diagnosis system for complex multivariate processes is presented. The new proposal is based on Multiclass Support Vector Machines (MCSVM) and the case study was addressed to the automotive industry. A comparison against a similar technique is carried out. Simulation of the new proposal shows promisory results.

Comparison of Hospital Length of Stay, Costs, and Readmissions Among Patients With Occluded Central Venous Catheters Receiving Alteplase Versus Catheter Replacement

The present study explores features of policy, management and legislation (PML) that may facilitate country's sustainable development with the account of business demands in national governance. The paper discusses former attempts to measure PML related aspects from the perspective of sustainability at different levels. In order to get business strategies function in harmony with sector and national strategies in a sustainable manner, a framework interconnecting PML and business is required. There are numbers of methodologies, including sophisticated criteria systems, elaborated to measure PML in terms of sustainability. However, none of these methodologies correspond to linkages among PML sustainability and business demands. Therefore, the paper aims to construct conceptual framework requirements for sustainable governance and explain effects of such requirements on business.Results of research indicate the hierarchy of measurable and aggregated overlapping criteria for evaluation of PML domains of sustainable strategy of a country. Among the most significant parameters are political, managerial and legitimate inclusion, level of corruption, balance of evidence based policy practice, process transparency, balance of interests, open process monitoring system, etc. These criteria represent principles of public in general and business in particular inclusion, rule of law and integrated solidarity based management that should be achieved for strategically driven sustainable development. Business motivation and engagement, stable and favorable political, procedural and legal environment, long-term strategy support via regulation, and other features of PML could secure sustainability of business strategy.

Bridging Political, Managerial and Legislative Components of Sustainability Strategy with Business Demands

The present study explores features of policy, management and legislation (PML) that may facilitate country's sustainable development with the account of business demands in national governance. The paper discusses former attempts to measure PML related aspects from the perspective of sustainability at different levels. In order to get business strategies function in harmony with sector and national strategies in a sustainable manner, a framework interconnecting PML and business is required. There are numbers of methodologies, including sophisticated criteria systems, elaborated to measure PML in terms of sustainability. However, none of these methodologies correspond to linkages among PML sustainability and business demands. Therefore, the paper aims to construct conceptual framework requirements for sustainable governance and explain effects of such requirements on business.Results of research indicate the hierarchy of measurable and aggregated overlapping criteria for evaluation of PML domains of sustainable strategy of a country. Among the most significant parameters are political, managerial and legitimate inclusion, level of corruption, balance of evidence based policy practice, process transparency, balance of interests, open process monitoring system, etc. These criteria represent principles of public in general and business in particular inclusion, rule of law and integrated solidarity based management that should be achieved for strategically driven sustainable development. Business motivation and engagement, stable and favorable political, procedural and legal environment, long-term strategy support via regulation, and other features of PML could secure sustainability of business strategy.

An on-line monitoring system for wire electrical discharge turning process

This article presents a new pulse discriminating system for process monitoring of wire electrical discharge turning. The pulse discriminating device, including a spark gap monitor and a digital signal processor card, has been developed to identify four major gap states classified as open circuit, normal spark, arc discharge and short circuit based on the characteristics of gap voltage waveform as well as compute ignition delay time for each open circuit and normal spark. By means of this system, the proportion of open circuit, normal spark, arc discharge and short circuit to total sparks and average ignition delay time within a time interval of 200 ms can be analyzed quantitatively during the wire electrical discharge turning process. It has been observed that thread cutting using wire electrical discharge turning exhibited more stable machining than cylindrical wire electrical discharge turning under a servo feed machining condition because servo feed control of the cylindrical wire electrical discharge turning process only focused on keeping forward sparking gap at a proper width, but it failed to respond to the variation of lateral gap width due to an independent motion of the rotary axis with respect to the translational axis. Experimental results also demonstrate that these pulse train data and average ignition delay time can substitute for average gap voltage as sensing parameters for on-line monitoring and control of the wire electrical discharge turning process.

Industrial Crystallization

Crystallization is one of the most widely used technologies in chemical industry; especially the food and pharmaceutical sectors are utilizing this unit operation for optimized separation, purification, and solid form selection. In addition to the unique advantage that crystallization can produce the crystalline product with a high purity, crystallization also plays an essential role in other aspects of the final product design. This is widely applied in the selection of the optimal solid forms in the pre-formulation and formulation of pharmaceutical products as well as in the optimization of the particulate properties, such as particle size and shape distributions. During the past decades, significantly increased efforts have been made towards the exploration of the solid form landscape that covers all possible solid structures, such as polymorphs, solvates, co-crystals, salts, and increasingly also amorphous phase. These increased activities are driven by the existing challenges in the pharmaceutical industry regarding the increased number of drug candidates with poor physicochemical profile, e.g., solubility in biological fluids. Meanwhile, the development of crystallization processes represents a complex and challenging issue, where several product properties, such as purity, crystal size and shape, and molecular level solid structure, have to be controlled simultaneously. The International Workshop on Industrial Crystallization (BIWIC) was initiated by Prof. Joachim Ulrich in 1990. A successful series of meetings have been held in the yearly workshop in Bremen, Delft, Halle, Rouen, Gyeongju, Cape Town, Magdeburg, Lappeenranta, and Tianjin. The 20th event, BIWIC 2013, was hosted by Dr. Haiyan Qu and Prof. Jukka Rantanen at the University of Southern Denmark in Odense, Denmark. Over the last two decades, BIWIC has developed into a highly successful and internationally recognized workshop for the industrial crystallization community. This special issue of Chemical Engineering & Technology combines selected contributions of BIWIC 2013 with other outstanding publications in the field of industrial crystallization. A wide range of interesting topics that address inter-disciplinary research issues is covered. In addition to the significant number of contributions devoted to the crystallization of different polymorphic compounds, solvates, and salts, novel formulation technologies involving the utilization of printable medicine products are also presented. Fundamental topics include nucleation and crystal growth kinetics, as well as modeling of crystallization processes. The new challenges in crystallization process control and scale up are discussed in the contributions dealing with in situ process monitoring and process analytical technology (PAT) system design. The crystallization of inorganics, organics, and proteins are covered in the articles concerned with the production of crystalline products in chemical food and pharmaceutical industry. Surprisingly, the so-called old topics are indeed the new topics, since the turn towards natural resources for chemicals, foods, and pharmaceutical materials lead to new challenges in separation and purification of those compounds. Crystallization is, at the end of the day, one of the most promising technologies for those challenges. Haiyan Qu, University of Southern Denmark Jukka Rantanen, University of Copenhagen Joachim Ulrich, Martin Luther University Halle-Wittenberg

In situ low-cost and adaptable braze tool evaluation system with vision analysis

In this study, a low-cost, flexible process monitoring system for focussed arc tungsten inert gas welder tool electrodes is presented. The system is capable of acquiring and processing geometric data that are used to define acceptance criteria. This system is used to characterise tool wear phenomena in repetitive brazing runs ensuring that the tool is operating within its process window. It was found, using this apparatus, that a build-up of zinc oxide, originating from the zinc-coated steel, on the braze tool prohibits arcing and delivery of a good quality joint. The vision system can identify build-up of this layer before failure of ignition. Measurements showed that after 990 s of continuous arcing, the zinc oxide build-up would cause system malfunction. The vision system gave a warning of zinc build-up at 577 s.

Occurrence-Oriented Design Strategy for Developing Business Process Monitoring Systems

In a competitive market, business process improvement is a requirement for any organization. This improvement can only be achieved with the support of comprehensive systems that fully monitor business processes. We propose an occurrence—based approach to business process monitoring that provides a holistic perspective of system dynamics, lending support to evolution aspects. More specifically, we present a three-dimensional artifact, called Occurrence, in which structure, behavior, and guidance are considered simultaneously. Based on this, we define more complex structures, namely Occurrence Base and Occurrence Management System, which serve as scaffolding to develop business process monitoring systems. We also present a specific occurrence-based design strategy that, using an MDE approach, has been applied by our research group for the development of successful monitoring applications.

Monitoring and Adaptive Process Control of Wire Electrical Discharge Turning

This paper presents a novel pulse discriminating and control system for the identification of spark gap states, process monitoring and control of Wire Electrical Discharge Turning (WEDT). The relation between the proportion of open circuit, normal spark, arc discharge, short circuit to total sparks (defined as open circuit ratio, normal spark ratio, arc discharge ratio and short circuit ratio, respectively), ignition delay time and metal removal rate were experimentally studied and analyzed. A fuzzy logic controller was proposed to control both the arc discharge ratio and ignition delay time at optimal levels by on-line regulation of table feed-rate and pulse off-time for adaptive control optimization of WEDT. Experimental results show that the developed process monitoring and control system results in faster machining and better machining stability as compared with a conventional servo feed control scheme for the WEDT process.

Situation prediction based on fuzzy clustering for industrial complex processes

Prediction of process behavior is important and useful to understand the system status and to take early control actions during operation. This paper presents a fuzzy clustering approach for predicting situations (functional states) in complex process industries. The proposed methodology combines a static measurement, such as the result of a fuzzy classifier trained with historical process data, and an estimation algorithm based on Markov‘s theory for discrete event systems. The situation prediction function is integrated into a process monitoring system without increasing the computational cost, which makes real-time implementation feasible. The monitoring strategy includes two principal stages: an offline stage for designing the fuzzy classifier and the predictor, and an online stage for identifying current process situations and for estimating predicted functional states. Thus, at each sample time, the results of a fuzzy classifier are used as inputs in the prediction procedure. An attractive feature of our proposed method, for situation prediction, is that it provides information about the evolution of the process. The proposed approach was tested on a monitoring system for a power transmission line, and also for monitoring a boiler subsystem of a steam generator. Experimental results indicate that our proposed technique in this paper is effective and can be used as a tool, for operators, to be used in industrial process decision making.

Adaptive shape control of laser-deposited metal structures by adjusting weld pool size

LMD (Laser Metal Deposition) is a technique used to repair damaged components and directly form three dimensional structures. From the aspect of productivity, improvement of the shape accuracy of the deposit is required to reduce machining process after LMD. Objective of this work is to control the build-up shape by adjusting the weld pool size. Configurations of deposits made with various LMD process conditions were measured in cross section. In addition, the signal intensity of heat radiation, plume emissions and laser reflections from the weld pool was monitored by photodiodes intergrated in laser processing head during LMD process. The results showed a strong correlation between weld pool size and signal intensity of heat radiation. Adaptive shape control system, which consists of in process monitoring system and PID (Proportional-Integral-Derivative) controller using that correlation, was developed to control build-up shape. Due to the liner relationship with weld pool size, laser power was selected as the PID output parameter adjusted by the heat radiation signal. Since the target value of the heat radiation signal can be changed flexibly during the LMD process in our PID control system, deposit shape is successfully controlled as required with sufficient profile accuracy of the build-up layers.

Can airborne ultrasound monitor bubble size in chocolate?

Aerated chocolate products consist of solid chocolate with the inclusion of bubbles and are a popular consumer product in many countries. The volume fraction and size distribution of the bubbles has an effect on their sensory properties and manufacturing cost. For these reasons it is important to have an online real time process monitoring system capable of measuring their bubble size distribution. As these products are eaten by consumers it is desirable that the monitoring system is non contact to avoid food contaminations. In this work we assess the feasibility of using an airborne ultrasound system to monitor the bubble size distribution in aerated chocolate bars. The experimental results from the airborne acoustic experiments were compared with theoretical results for known bubble size distributions using COMSOL Multiphysics. This combined experimental and theoretical approach is used to develop a greater understanding of how ultrasound propagates through aerated chocolate and to assess the feasibility of using airborne ultrasound to monitor bubble size distribution in these systems. The results indicated that a smaller bubble size distribution would result in an increase in attenuation through the product.

Process Monitoring System Based on Anomaly Detection Statistics Algorithm

In order to find more efficient and handle the internal network threat with the LAN network threat warning and real-time processing, remote process monitoring and management of computer systems is used in this paper. By getting the system process handle on the local computer, realizes the acquisition of the threat source information of the system. By customization of the application layer protocol AMCP, realizes the efficient information transmission between server and client. In order to enhance the reliability of the system security threat model, the System security threat information is analysised with the anomaly detection algorithm based on statistics. Analysis of the test data shows that: through getting the system process handle on the local computer, the system treating information can be obtained. Through the security threat model based the anomaly detection algorithm based on statistics, network threat is dealed efficiently and real time.

Improved two-level monitoring system for plant-wide processes

In modern industries, the plant-wide process has become more and more popular, which always consists of various operation units, equipments, workshops and even factories. Therefore, it is more difficult to monitor those processes, and the monitoring complexity is also much higher. While the traditional multivariate statistical analysis provides satisfactory monitoring results within a single part, e.g. operation unit, it may fail to catch the detailed cross-information among different parts of the process. In this paper, an improved two-level monitoring system is formulated for plant-wide processes. In the first level, the latent variable information is extracted by the principal component analysis (PCA) model, based on which a global latent variable matrix is generated by combining latent variables from different parts of the process. In order to characterize the cross-data information of the plant-wide process, an efficient support vector data description (SVDD) method is employed for modeling the relationships among the global latent variable matrices. Based on the results of the Tennessee Eastman (TE) process, an enhanced performance is obtained by the improved two-level monitoring system. Compared to the traditional PCA based monitoring strategy, the new method is useful to describe the cross-data information of the plant-wide process, based on which more accurate monitoring results can be obtained.

Self-tuning of Teachless Process Monitoring Systems with Multi-criteria Monitoring Strategy in Series Production

Abstract Modern monitoring systems in machine tools are able to detect process errors promptly. Still, the application of monitoring systems is restricted by the complexity of parameterization for save monitoring. In most cases, only specially trained personnel can handle this job at multi-spindle machines or turn-mill centers. The aim of the research project “Proceed” is to figure out in which extent a self-parameterization and independent optimization of monitoring systems in industrial series production can be realized. Therefore, the complete parameterization of the processing chain, consisting of the choice of signal sources, character extraction, the monitoring- and decision making strategy, shall be automated. This paper deals with the self-parameterization of a multi-criteria monitoring system based on a genetic algorithm.

Adaptive SOA Stack-Based Business Process Monitoring Platform

Executable business processes that formally describe company activities are well placed in the SOA environment as they allow for declarative organization of high-level system logic.However, for both technical and non-technical users, to fully benet from that element of abstractionappropriate business process monitoring systems are required and existing solutions remain unsatisfactory.The paper discusses the problem of business process monitoring in the context of the service orientation paradigm in order to propose an architectural solution and provide implementation of a system for business process monitoring that alleviates the shortcomings of the existing solutions.Various platforms are investigated to obtain a broader view of the monitoring problem and to gather functional and non-functional requirements. These requirements constitute input forthe further analysis and the system design. The monitoring software is then implemented and evaluated according to the specied criteria.An extensible business process monitoring system was designed and built on top of OSGiMM - a dynamic, event-driven, congurable communications layer that provides real-time monitoring capabilities for various types of resources. The system was tested against the stated functional requirements and its implementation provides a starting point for the further work.It is concluded that providing a uniform business process monitoring solution that satises a wide range of users and business process platform vendors is a dicult endeavor. It is furthermore reasoned that only an extensible, open-source, monitoring platform built on top of a scalablecommunication core has a chance to address all the stated and future requirements.

Building a Smooth Medical Service for Operating Room Using RFID Technologies

Due to the information technology advancement, the feasibility for the establishment of mobile medical environments has been strengthened. Using RFID to facilitate the tracing of patients’ mobile position in hospital has attracted more attentions from researchers due to the demand on advanced features. Traditionally, the management of surgical treatment is generally manually operated and there is no consistent operating procedure for patients transferring among wards, surgery waiting rooms, operating rooms, and recovery rooms, resulting in panicky and urgent transferring work among departments and, thus, leading to delays and errors. In this paper, we propose a new framework using radio frequency identification (RFID) technology for a mobilized surgical process monitoring system. Through the active tag, an application management system used before, during, and after the surgical processes has been proposed. The concept of signal level matrix, SLM, was proposed to accurately identify patients and dynamically track patients’ location. By updating patient’s information real-time, the preprocessing time needed for various tasks and incomplete transfers among departments can be reduced, the medical resources can be effectively used, unnecessary medical disputes can be reduced, and more comprehensive health care environment can be provided. The feasibility and effectiveness of our proposed system are demonstrated with a number of experimental results.