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In this work, three passive techniques (ferrofluid, porous zone, curved surfaces) have been merged with one active technique (electric force) to enhance the convective rate. The permeable enclosure contains two curved walls and two straight walls which are not stationary. The concentration of ferrofluid within the domain is constant and associated formulations for properties of ferrofluid have been applied in modeling in which no slip velocity exists among particles. With define, measure, analyze, improve and control (DMAIC), the vorticity equation for partial equations which contain the source terms of electrohydrodynamic (EHD) and permeability, final equations have been achieved and for finding the solution combination of two basic techniques were utilized. Low deviation with a prior article in the validation procedure indicated a good agreement. Nu can augment around 0.49% if platelet particles were applied rather than sphere. Utilizing radiation in simulation makes Nu augment around 82.27%. Elevating Da in the absence and appearance of EHD leads to an augment of Nu around 145.01% and 393.38%. Appearance of EHD enhances the Nu about 96.04%.

Machine vision technology has attracted a strong interest among Finnish research organizations, which has resulted in many innovative products for industry. Despite this goal users were very skeptical towards machine vision and its robustness in harsh industrial environments. Therefore the Technology Development Centre, TEKES, which funds technology related research and development projects in universities and individual companies in Finland, decided to start a national technology program, "Machine Vision 1992–1996".

Led by industry, the program boosts research in machine vision technology and seeks to put the research results to work in practical industrial applications. The emphasis is on nationally important, demanding applications. The program will create new business for machine vision producers and encourage the process and manufacturing industry to take advantage of this new technology. So far 60 companies and all major universities and research centers in Finland are working on our forty different projects. The key themes are Process Control, Robot Vision and Quality Control.

Refining and petrochemical processing facilities utilize various process control applications to raise productivity and enhance plant operation. Client–server communication model is used for integrating these highly interacting applications across multiple network layers utilized in distributed control systems. This paper presents an optimum process control environment by merging sequential and regulatory control, advanced regulatory control, multivariable control, unit-based process control, and plant-wide advanced process control into a single collaborative automation platform to ensure optimum operation of processing equipment for achieving maximum yield of all manufacturing facilities. The main control module is replaced by a standard real-time server. The input/output racks are physically and logically decoupled from the controller by converting them into distributed autonomous process interface systems. Real-time data distribution service middleware is used for providing seamless cross-vendor interoperable communication among all process control applications and distributed autonomous process interface systems. Detailed performance analysis was conducted to evaluate the average communication latency and aggregate messaging capacity among process control applications and distributed autonomous process interface systems. The overall performance results confirm the viability of the new proposal as the basis for designing an optimal collaborative automation platform to handle all process control applications. It also does not impose any inherent limit on the aggregate data messaging capacity, making it suitable for scalable automation platforms.

Automated generation of test cases is a prerequisite for fast testing. Whereas the research in automated test data generation addressed the creation of individual test points, test trajectory generation has attracted limited attention. In simple terms, a test trajectory is defined as a series of data points, with each (possibly multidimensional) point relying upon the value(s) of previous point(s). Many embedded systems use data trajectories as inputs, including closed-loop process controllers, robotic manipulators, nuclear monitoring systems, and flight control systems. For these systems, testers can either handcraft test trajectories, use input trajectories from older versions of the system or, perhaps, collect test data in a high fidelity system simulator. While these are valid approaches, they are expensive and time-consuming, especially if the assessment goals require many tests.

We developed a framework for expanding a small, conventionally developed set of test trajectories into a large set suitable, for example, for system safety assurance. Statistical regression is the core of this framework. The regression analysis builds a relationship between controllable independent variables and closely correlated dependent variables, which represent test trajectories. By perturbing the independent variables, new test trajectories are generated automatically. Our approach has been applied in the safety assessment of a fault tolerant flight control system. Linear regression, multiple linear regression, and autoregressive techniques are compared. The performance metrics include the speed of test generation and the percentage of "acceptable" trajectories, measured by the domain specific reasonableness checks.

Polishing process has not been thoroughly understood. The current practice of determining parameter setting for polishing process is done by trial and error approach and subjective experience of polish experts. This may not lead to optimal parameter settings. In this paper, Taguchi method is proposed to determine optimal parameter setting for rough polishing of stainless steel. Experiments are designed using orthogonal arrays. The optimal setting is obtained through average level analysis. Confirmation experiment showed that the roughness is satisfactory.

A number of authors have considered the procedure of online process control in which every $h$th item produced is inspected. The process is judged to be in control and continues if the inspected item is judged to conform to specifications. If the inspected item is judged to be nonconforming, then the process is judged to be out of control and stopped, examined, and adjusted as necessary. This inspection process is subject to misclassification and different schemes have been suggested for dealing with this. In this paper, we propose a new rule in which the final judgment that an item is conforming, and thus the process is in control, if and only if $k$ consecutive classifications as conforming occur before a total of $f$ classifications as nonconforming. We will examine various aspects of this protocol and provide advice on how to determine values of $k$ and $f$ for this rule.

Nowadays, business collaborations have to be highly dynamic and flexible to allow companies to operate efficiently and effectively in complex and volatile markets. To increase the business agility of service consumers, it is fundamental that service providers enhance the visibility of parts of their collaborative processes. Service providers are required to release both the process structures of the services offered and their status during execution. To further increase the flexibility of business collaborations, certain control over the process execution has to be offered to service consumers. In this paper, we present a framework for the support of process control in cross-organizational settings. We specify the control primitives that can be used to exert control on activities and processes before, during and after their executions. These primitives empower service consumers to postpone activity and process executions, bypass minor activities, repeat their executions, etc. We describe an approach to the support of these control primitives by service providers. We demonstrate the application of our framework with a case study from the healthcare domain. A proof-of-concept prototype implementation based on Web service technology is presented.

Diabetes mellitus is a heterogeneous clinical syndrome characterized by hyperglycemia and long-term specific complications: retinopathy, neuropathy, nephropathy, and cardiomyopathy. Automatic neuropathy leads to visceral denervation producing a variety of clinical abnormalities: cardiac and respiratory dysrythaemias, gastrointestinal motility disorders, urinary bladder dysfunction and impotence. Diabetes mellitus is a leading cause of blindness; renal failure and limb amputation all over the world. The need to detect diabetic risk factors and treat organ disorders and complications associated with diabetes provides the impetus for us to develop the technology for assessment of diabetes, its etiology and severity, as well as for assessing the efficacy of pharmacological therapy.

This paper concerns:

(i) modelling of blood-glucose regulation and tolerance-testing,

(ii) demonstrating patient-simulation of the blood-glucose regulatory models, by means of which the model parameters can be evaluated and related to physiological parameters, and

(iii) elucidating how the glucose-regulatory system model's pole-zero representation and the blood glucose-insulin transfer-function can explain the blood glucose response data in intravenous and oral glucose tolerance tests.

An easy-to-implement simple clinical-application method is developed to simulate the response of the blood-glucose regulatory model in diabetic patients during intravenous glucose tolerance test and to estimate the model parameters, which can then enable differential diagnosis of diabetes and its severity as well as in early detection of risk-to-diabetes.

In the oral glucose-tolerance test, the role of the gut is to facilitate transport of glucose across the intestinal wall. The Michaelis-Menten equation, describing this enzyme-catalyzed reaction rate, can be employed to conclude that the intestinal glucose absorption rate into the blood-compartment from the gut during the oral glucose-tolerance test is constant, almost resembling a rectangular pulse Nevertheless, we have formulated a new rate-control model to simulate the oral glucose-tolerance test data, by means of the response-function of a second-order system of a single-compartment (consisting of the gut and the blood-glucose pool), with the oral glucose-bolus as the impulse-input.

We have also demonstrated application of this rate-control model to patients undergoing oral glucose-tolerance test, to evaluate the model parameters. By categorizing the ranges of these parameters for normals and diabetics (varying from mild to severe), we can reliably apply this model and procedure clinically.

Microfluidic droplets formed in emulsions are used in a variety of analytical techniques and hold great potential for future scientific and commercial applications. Our experiments present a microdroplet generation and consistency monitoring system with laser optics excitation and detection. We also demonstrate the detection of cancer cells encapsulated within aqueous microdroplets in continuous oil phase flow. The custom setup analyzes each droplet with sub-millisecond signal resolution and single photon accuracy, and is compatible with process-monitoring methods. To demonstrate the consistency of microdroplet generation over time, we measure and examine the mean frequency of aqueous plug-shaped droplet (microplug) formation in oil phase, as well as the mean length and interval between consecutive droplets. Two-channel optical monitoring allows for the simultaneous and independent inspection of both microdroplet generation and identification of green fluorescent protein-labeled cancer cells within the droplets. A precise, quantitative approach as utilized in these experiments may be helpful in the development of microfluidic concepts that require exacting reproducibility and would benefit from automated consistency monitoring techniques.

This paper introduces the concepts of off-line and on-line quality control. It goes on to explain in some detail off-line and on-line quality control techniques. It shows that, when applied properly, these techniques can generate the desired results in any manufacturing environment. The paper will also refer to statistical process control-related activities in the assembly plant of Motorola at Austin, Texas.

To address the problems of customized design, unclear functional interfaces between modules, and complex process control logic in the autonomous operation process control of power robots, this chapter proposes a standardized job file based on XML format for power robot operation task process control, From the perspective of general generality and top-level unified management, a universally applicable control method for the operation process of electric robots was studied. Through hierarchical design, job tasks are subdivided into task items, job items, action items, and other subcategories in standardized format, which improves the flexibility of job sequence configuration and forms job files with complete task information. Corresponding to the hierarchy of job files, a multi-layer finite state machine software framework is designed, combined with job file information, to achieve clear interactive scheduling management of upstream and downstream multi-modules in the job process. This method solves the problems of weak adaptability, low flexibility, and complex control logic in the task flow control components and methods of power robots, and improves the reusability and portability of software functional modules. The application analysis of the autonomous operation of transmission line inspection robots shows that compared with conventional methods, this method can effectively improve the efficiency of operation process control and has good generalization ability for different types of job tasks.

Petri nets are a powerful tool for visual representation of complex software engineering and knowledge engineering problems, and for analysis of their dynamic behavior. This survey consists mainly of practical examples, which include the use of time Petri nets. Petri nets have well-defined semantics, and can be used to interpret textual languages, particularly for communication and coordination. We explore one such application in detail. The nets can grow too large for human comprehension; some suggestions are given on how to deal with this problem. We also look at fuzzy reasoning based on Petri nets.

Machine vision technology has attracted a strong interest among Finnish research organizations, which has resulted in many innovative products for industry. Despite this goal users were very skeptical towards machine vision and its robustness in harsh industrial environments. Therefore the Technology Development Centre, TEKES, which funds technology related research and development projects in universities and individual companies in Finland, decided to start a national technology program, “Machine Vision 1992-1996”.

Led by industry, the program boosts research in machine vision technology and seeks to put the research results to work in practical industrial applications. The emphasis is on nationally important, demanding applications. The program will create new business for machine vision producers and encourage the process and manufacturing industry to take advantage of this new technology. So far 60 companies and all major universities and research centers in Finland are working on our forty different projects. The key themes are Process Control, Robot Vision and Quality Control.

It is argued that the primitives currently available to synchronise resource accesses are of limited usefulness for real-time applications, since they fully disregard the notion of time and are difficult to apply. Therefore, an adequate concept is devised in analogy to the synchronisation practice in other areas, and especially in everyday life, which is fully based on the dimension time.

Monitoring chemical reactions is the key to chemical process control. Today, mainly optical online methods are applied, which require excessive calibration effort. NMR spectroscopy has a high potential for direct loop process control while exhibiting short setup times. Compact NMR instruments make NMR spectroscopy accessible in industrial and harsh environments for advanced process monitoring and control, as demonstrated within the European Union’s Horizon 2020 project CONSENS.

We present a range of approaches for the automated spectra analysis moving from conventional multivariate statistical approach, (i.e., Partial Least Squares Regression) to physically motivated spectral models (i.e., Indirect Hard Modelling and Quantum Mechanical calculations). By using the benefits of traditional qNMR experiments data analysis models can meet the demands of the PAT community (Process Analytical Technology) regarding low calibration effort/calibration free methods, fast adaptions for new reactants or derivatives and robust automation schemes.

In this paper we show that there appears to be an abundance of universal fuzzy controllers. A universal fuzzy controller is a type of fuzzy controller that can control any controllable process.

On the basis of risk management, this paper construct the product quality safety risk process control mechanism which include feed forward control phase, concurrent control phase and feedback control phase through the PDCA cycle control. For the new mechanism of the supervision of product quality and safety, the core is risk management, the focus is on quality and safety risk prevention. The new mechanism will promote the development of the product quality and safety management system and the management ability.