Industrial Applications of Computers - Case Study Example

Industrial Application of Computers Computer System for the Proposed Paperboard Production Facility Plug-and-play Network Technology for a Quality Control System Introduction For a company that excels in providing just-in-time customer services, there is a need to incorporate a computer integrated production system into its facilities to realize a just-in-time operation for both the ordering and manufacturing paperboards. A computer generated production system is simply an approach that uses computers to facilitate the control of the entire processes of production as well as managing the production process by users in different departments. By integrating a computer system into the production process, the manufacturing can be faster and prone to minimal errors in addition to creating an automated manufacturing process. The paperboard industry is under pressure to reduce their costs for manufacturing in respond to the conditions of the market. Because of this, the paper industry has embarked on restructuring their systems of production that will see to boosting their profitability and ensure a stable operations and efficiency in maintenance. The paperboard machines are essential for proper manufacturing; however, the machines are challenged in their stable operations to meet the product specifications. To enable the paperboard company meet its market demands, development of a plug-and-play quality control system (QCS) that will optimize services for the paper machine is recommended. Profitable papermaking means continuous production with minimal deviations from quality specifications. While steady-state control performance is essential, the elimination of waste during transitions such as changes of grades and break recoveries is where the greatest economic gains can be achieved. As production rates rise, often stretching the design capacity of the paper machine, Quality Control Systems (QCS) allow the company to improve the efficiency and quality of the production. This is evident from the significant new developments in quality measurement and control since the introduction of cross direction (CD) control seen in the past years since the 1970s. For paperboard manufacturing using the paper machines, it is necessary to establish the control system that provides a high-mix, low-volume product production. Control parameters are the key component of optimizing the operation, and so the paperboard company should consider an advanced performing QCS. In many cases, the control parameters of paperboard production facilities are normally fixed to the same value using a typical product. Many of these paper production facilities operates in a high mix, low-volume condition because the equipment are consolidated and diverse products are produced to satisfy the end user’s request. Moreover, the paperboard production equipment is often disturbed by the processes of feed preparation or by auxiliary systems. It is for this reason that the control parameters require optimization by deploying a plug-and-play quality control system. Plug-and-play Quality Control System Network Diagram The plug-and-play QCS is a cost effective tool that is used to monitor and control the processes of producing the paperboards. The QCS will consist of a scanner that is driven by a logic controller that is programmable, measurement sensors that are network-ready and a station for operations which is connected to a high speed Ethernet network. The architecture provides unlimited connectivity that helps in configuring the system as part of the mill wide distributed control system for full integration into the business network (Oloufa & Thomas, 1999). The configured system featured an off-the-shelf software suite that is configured for high resolution cross the profiles of the equipment, providing historical trends, statistics as well as the supervisory controls of MD/CD. The QCS system is built with components that meet the standard of the industry providing a generic installation designed give self maintenance to the mill (Elleithy & Sobh, 2013). Selection of scanners and sensors is done and they are specified for various applications including paperboards and pulp machines. Scanner designs that are proven will ensure reliable performance of the paper mill with minimum maintenance required. In addition, the built-in internet access allows for remote diagnostics and technical support (Fraser, 2001). The plug-and-play QCS technology will have the scanner driven by an off-the-shelf logic controller, which is already programmed, and will perform the scans, fixed points, off sheets, standardization of sensors and scanning platform service functions. The measurement sensors will have network ready gauges which are fully intelligent (Fraser, 2001). They will use a signal processor based in a microcontroller and data communications controller. This high speed conversion of analogue to digital process will ensure a fast sensor response during delivering of optimum signal to noise ratio. The heads of the sensors will be equipped with vortex cooling and air knives for applications where there are hostile environmental conditions. The industrial Ethernet communication protocol is used to make the sensors and scanners the basic building blocks for the connecting plug-and-play quality control system to a human machine interface, for example the standard PC platform. However, a number of protocols can be supported by the system such as Modbus Ethernet and Ethernet/IP. The Ethernet communication protocols are the structures used within a communication system so that computers at the control room can easily communicate with the processes of production. Standardization of the communication protocol is significant so that a more integrated instrumentation and control system can be developed. in plug and play quality control system, acquiring of data is through instrument measurement, which are transmitted to a controller, a computer, which then transmit control signals to control devices. Integration of these systems with each other enables quick and effective transfer of data in a quality control system, which facilitates both the quality and productivity. The sensor controllers supports a number of gauges, which includes nuclear gauge for weight and ash measurement, microwave and infrared gauges responsible for measuring moisture, laser gauges that measures calliper. The profile of the cross machine direction and measurement data calibrated in the units of the engineering are processed at the sensors and transferred for display, control and archiving in the computer. The quality control system has the capability of integrating with an industrial SCADA system and PLC control panels to have a PC/PLC automation platform for display operation, data archiving, reporting, machine control supervisory and easy connection with external systems. Design Methodology The automatic quality control system is the significant part of a quality control in a mill of a single paperboard machine. The software and maintenance services thus are specifically used for quality control purposes (Holik, 2013). Principally, quality control components consist of process stations, operator stations and scanners. These components are integrated in a computer system network as shown in the figure below; Process and operator stations are the common commercial computers connected with each other through a modified IP/TCP protocol system bus (Elahi, 2006; Laubach, 2001). Some of the process stations can be dedicated to quality control software and others to the quality measurement scanners and the normal instrumentation (Walker, 1998). It is through the field buses that the scanners communicate with the operator stations. The machine direction (MD) may automatically control the paperboard quality variables such as weight, moisture and fibre orientation using the feedback control loops. However, the controllability of the MD is dependant mainly on the time delay between the measurement and the actuator. The control loops at the MD are cascading, having lower level and upper level advanced loops. The principle of periodic measurement traversing the position of scanners and remote actuator from measuring devices implies long time delay. This can be partly compensated by a model predictive control algorithm at the upper level. Multivariable control strategies are however recommended due to the strong interaction experienced between the different controllable variable. The central operation in paperboard making is the scanning platform through which the paper rolls passes. The scanner holds an assembly of sensors which measure the principle properties of paperboard such as weight and moisture as they pass across the sheet. A set of sophisticated control algorithm then instruct the regulation of the paper machine. Quality control system user interface displays are an integral part of the System Platform. Quality control objects and aspects provide information associated with paper machine quality control. A user can control all of the papermaking process from one location. Easy to use displays are provided for machine operators (Hardy, 2001). You can instantly view high resolution measurements, machine-direction and cross-direction variations, profile contour maps, reel reports, grade reports, documentation, and support tools. All data are easy to export to standard spread sheets for convenient data capture and analysis. Having access to real-time quality control information enables better process decisions; reducing waste, saving raw material and ultimately increasing shareholder value. Computer optimization is utilized in large-scale multivariable cross direction (CD) algorithm that has feedback control loops. The utilization is done for numerous measurement points and actuators to minimize errors at the CD profile. Actuator spacing varies from 25mm to 150mm, which aid in setting the lower limit of the CD controllability. The QCS is installed in the purchaser’s mill. A system platform with its scanners, sensors, computers, monitors, system racks, networks and cables are installed. The tested system and application software is loaded into the operator and process modules and servers. After the installation process machinery and piping trials, instrumentation calibration inspections and wired protection electronics trials, signal and loop testing should be done accordingly. Evaluation of the quality control system can be done with respect to its dependability, functionality, operability and other properties that are non-task related. Discussing an advanced control system is done in relation to control process, quality control, maintenance, and process development (Quevauviller, 1995). The functionality of the whole QCS is evaluated. In a cold commissioning, a paperboard machine is run with water. In a hot commissioning, a paperboard machine is started up with real pulps and chemicals. The QCS application software for every process section is checked, the control loop tuning and parameter optimizing are performed. Often the 2-sigma deviations of CD profiles and MD trends are monitored. External foil samples and offline roll samples may be used as a reference for calibration. After the commissioning procedures, a final system acceptance test (SAT) is performed to show that the QCS works according to its functional descriptions in a full production load. The performance indices are compared with the values given in the functional descriptions. Possible Option Analysis To validate the QCS, referring to the quality assurance of the mill, may require the use of an offline web analysis as another option. This analysis will begin at the specification phase of the QCS project, to validation phase and finally to the production phase. The variation of quality variables can be categorized into three that is cross direction variation, machine direction variation and finally the residual variation. Samples taken from the ready rolls can be analysed using the lab analysers; however, only the residual and cross direction variances may be revealed. The company may require considering an advanced total paper analyser consisting of commercial scanners and measurement scanners with analysing software. The sensors included are weight basis, moisture, calliper, and fibre orientation. Wounding of paperboard roll may be done stepwise with a speed of up to 100m/min. in this mode, he CD profile may be then analysed with a 10mm by 10mm resolution. The traversing scanners measurement data move in a zigzag path where control direction profiles are absent. And here, the CD and MD profiles require estimation. This is so because the scanner’s measurement data in a quality control system are pre-processed for different purposes. For instance, there is an analogue system processing in the quality measurement sensors in scanners to attenuate the stochastic noise within the electronic sensors. Many a times, this analogue pre-processing cannot be adjusted by maintenance team. The CD and MD profile quality variable are pre-processed for display and operational purposes at the control room. The use of digital signal processing is evident since the databoxes of the CD profile may be averaged to the width of an actuator. Additionally, quality measurement data is processed separately for the purposes of quality control (Digitech, 1985). The MD and CD profiles require estimation; at the same time the CD profile averaged for actuator widths for control loops. Utilization of adjustable digital signal is evident, and reports concerning the improvement of CD and MD estimation using methods based on wavelet are evident (Dumont, 2004; p 15). Control performances on stability, convergence and tracking ability are obtained from the trends and reports on each of the QCS components, machine direction control, cross direction control and automatic grade change control. The obtained control performance of each component is evaluated by certain criteria and summarized as an analysis report. Paperboard machine conditions are also reported correlated with QCS data. The validation of the QCS system continues through the production process with different qualifications and ends at the validation phase. As long as traversing scanners are used in paperboard production, an offline QCS analysis helps the evaluation of quality control systems in validating of the production process. Signal processing of data measurement are taken into account when variation paperboard products as well as quality control system are evaluated using the online measurements. For the case study, the quality variable profile data of the paperboard machine are stored in an information system. Power spectral analyses can be used to look for periodic phenomena in the process. In the offline analysis after a system update, a clear peak of 5.8 Hz with the wavelength 1.23 m in a logarithmic variance spectral density function of MD basis weight and the MD variance of 0.9 (g/m2)2 were found. The share of the disturbance peak in the variance was 0.7 (g/m2)2. The disturbance was not seen in the QCS MD trends and its compensation is beyond the MD controllability. On this board machine, the variation wavelengths longer than 400 m could be monitored by the QCS. With the ATPA, the frequencies from 0.01 to 100 Hz in machine direction could be easily observed. In online systems, the MD trend calculation of quality variables is based on scanned data. Thus the calculation of MD variances from MD profile values does not give any new information. Scanners can be operated in a fixed point mode in order to get information on MD variations. This kind of evaluation may be used for calibration purposes, when the conformity of quality sensors and lab analyses is determined. In an offline quality control system, the processes are performed in a laboratory and other areas of production. The production processes are normally stopped and fabric inspections, laboratory and other tests are undertaken. Corrections are normally done according to the results from the tests. The offline quality control method is a systematic method of optimizing processes of production and product design at low cost. The option uses four key steps, which are identifying significant factors of the process that can be easily manipulated and their working level potential; performing factorial functional experiments using orthogonal array design on he processes; analysing the resulting data to come up with the maximum operating level of the factors; and conducting additional experiments to verify that the quality control is indeed improved by the new factor levels. The offline quality control method has distinctive features such as orthogonal arrays experimental designs and signal-to-noise ratio analysis that aid in providing economical way of studying how the production factors affects the mean and variance of the process. Quality control plays a significant role to the engineering and production industries. A company that wish to become a world class production industry need to understand, digest, disseminate and implement powerful tools as offline quality control system as an option. In addition, the company must also understand that quality control system is ensuring production of quality products which will satisfy the needs of the market and meet the present global competitiveness. Conclusion In the process of producing paperboards, many qualities of the product are controlled, as paper is used for a wide variety of purposes, and the controlled qualities vary from product to product. In the paper-making process, usually physical properties such as basis weight, i.e. weight per square meter, calliper and colour and chemical properties such as moisture and ash are measured on-line and controlled in a certain range depending on the paper product. Because the paper-making process is the final stage of the whole paper manufacturing process, the results of control in this process have a significant impact on the final product quality. Accordingly, optimizing control parameters of each control component such as machine direction (MD) control, cross direction (CD) control and grade change control depending on the paperboard product will greatly help stabilize the operation and thus improve the profits. The case study shows an overview of the paperboard-making process and typical control components of the QCS. Since a computer generated production system is an approach that uses computers to facilitate the control of the entire processes of production as well as managing the production process by users in a processing company, integration of a computer system into the production process will increase the speed of the processes of production and minimize the associated errors in addition to creating an automated manufacturing process. The paperboard industry is under pressure to reduce the costs of production to respond to the market conditions. Because of this, the paper industry should work towards on restructuring their systems of production that will see to an increase their profitability and ensure a stable operations and efficiency in maintenance. The paperboard machines are necessary for proper manufacturing; however, the machines are challenged in their stable operations to meet the product specifications. To enable the paperboard company meet the demands of the market, development of a plug-and-play quality control system (QCS) that will optimize services for the paper machine is recommended. References ELAHI, A., & ELAHI, M. (2006). Data, network, and Internet communications technology. Clifton Park, NY, Thomson Delmar Learning. LAUBACH, M. E., FARBER, D., & DUKES, S. D. (2001). Delivering Internet connections over cable breaking the access barrier. New York, John Wiley. http://search.ebscohost.com/login.aspx?direct=true&scope=site&db=nlebk&db=nlabk&AN=56785. HOLIK, H. (2013). Handbook of Paper and Board. Weinheim, Wiley. DUMONT, G., BALL, J., EMMOND, G., GUILLEMETTE, M. (2004). Improved CD control using wavelet-based MD/CD separation. Proc. PAPTAC Control Systems Conference, Quebec, Canada, pp. 57- 62 WALKER, N. E. (1998). The design analysis handbook a practical guide to design validation. Boston, Newnes. http://site.ebrary.com/id/10190358. QUEVAUVILLER, P., MAIER, E. A., & GRIEPINK. B. (1995). Quality assurance for environmental analysis method evaluation within the Measurements and Testing Programme (BCR). Amsterdam, Elsevier. http://www.sciencedirect.com/science/book/9780444899552 . DIGITECH '85, NORTHEASTERN CONFERENCE AND EXHIBIT ON INDUSTRIAL INSTRUMENTATION AND CONTROL. (1985). Process measurement and control: a reprint of process measurement and control papers presented at Digitech '85. Research Triangle Park, North Carolina, Instrument Society of America. FRASER, R. E. (2001). Process measurement and control: introduction to sensors, communication, adjustment, and control. Upper Saddle River, N.J., Prentice Hall. INTERNATIONAL JOINT CONFERENCES ON COMPUTER, INFORMATION, AND SYSTEMS SCIENCES, AND ENGINEERING, ELLEITHY, K., & SOBH, T. (2013). Innovations and advances in computer, information, systems sciences, and engineering. New York, NY, Springer. http://dx.doi.org/10.1007/978-1-4614-3535-8. DO, W.-S., OLOUFA, A. A., & THOMAS, H. R. (1999). Evaluation of global positioning system devices for a quality control system for compaction operations. Transportation Research Record. HARDY, W. C. (2001). QoS measurement and evaluation of telecommunications quality of service. Chichester, Wiley. http://search.ebscohost.com/login.aspx?direct=true&scope=site&db=nlebk&db=nlabk&AN=78935. Read More