Automation in the food processing industry

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The demand for high-quality product, the flexibility to share equipment to manufacture several products and other factors have moved the food industries towards ...
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Automation in the food processing industry: distributed control systems Michele Dahm and Anoop Mathur The demand for high-quality product, the flexibility to share equipment to manufacture several products and other factors have moved the food industries towards increased automation. Control system vendors have responded to these needs by providing appropriate hardware and modular software capability so the process engineer can concentrate on the process control strategy rather than the control system design. Also, the development of sensors that measure product quality and subjective properties such as taste, smell, etc., is providing new vistas in automation. This paper reviews the trends in sensors and control systems for the food processing industry. The advantages offered by the distributed control system (DCS) so far enjoyed by large, continuous process plants are now available to small users and to batch processing industries. Examples of DCS applications in the food industry are described. Keywords: Automation;

distributed

control system

INTRODUCTION Automating the food processing industry is becoming critical in today’s rapidly changing environment. Several factors are pushing the industry towards using automation, which may range from simple controls to highly sophisticated controls using advanced sensors capable of measuring intangible properties such as flavour, taste, smell, etc. These factors include: (1) increasing competition from globalization and mergers, (2) the consumer demand for higher quality goods, (3) higher emphasis on cleanliness and hygiene, (4) safety factors and the high costs of insurance and compensation, and (5) flexibility in manufacturing for more diversified product lines. For example, in today’s competitive market, it is not uncommon for manufacturers to change the processing conditions or formulation to provide a ‘new and improved’ version of their own existing products. This requires a control system with which the chemist or process engineer can easily modify the recipe. To remain competitive, the industry must build in Honeywell Inc., Sensor and System Development Center, 1000 Boone Avenue North, Golden Valley, Mn 55427, USA 32

manufacturing flexibility, allowing for greater product diversity and manufacturing yield, better quality control to satisfy customer requirements and tighter material flow control to contain product cost. Automating plant operations is one of the ways the industry can respond to these challenges (see Figure I ). Because of these new requirements, vendors are now Demand for higher quality

Domestic and international competition

Mergers / acquisitions

New product proliferation Figure 1

Challenges to the food and consumer industry

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Automation in the food industry: M. Dahm and A. Mathur Table 1

Today

Sensors for the food industrv

Pressure Temperature Flow Level Position Vibration Object recognition Colour Humidity Viscosity Turbidity Mass flow Specific ions Gas compositions

Tomorrow

Subjective properties - smell, tastes, testure, flavour Bionsensors - meat freshness Chemical sensors - acidity, sugar content

offering control systems that provide maximum flexibility, are easy to use and are capable of being incrementally built to the desired level of sophistication with open architecture that allows integration with existing equipment. This paper provides an overview of sensors and control systems for the food processing industry with emphasis on distributed control systems. It discusses the advantages offered by the distributed control system (DCS) so far enjoyed by large, continuous process plants and now also available to small users and to batch processing industries. It gives two examples of DCS applications in the food industry.

SENSORS FOR FOOD PROCESSING Sensors are the main interface between the control system and the process. In the food processing industry, sensors are required for the following: incoming material inspection; material waste control; process quality control; packaging inspection; equipment maintenance/failure prediction; environmental control. To fulfil the growing demand for low-cost, on-line, reliable sensors from the food industry, sensor development programmes designed to meet the specific needs of this industry are being established. Table 1 is a partial list of the sensors most often required for food processing. A good description of specific sensors for the food industry is provided in the literature (Smith, 1989; Smith, 1988; Sensors Review, 1989; Mans, 1988; Paulus, 1987; Opie,1987; Abdelrahman, 1988; Clark, 1986). Of real importance in the near future for automation in the food industry will be the use of sensors for in-line quality monitoring and control. These include: sensing of subjective properties such as softness, flavour, smell, taste, texture etc. and the development of new biosensors, chemical sensors and immunosensors such as sensors for meat freshness assessment, sugar content of fruit and vegetables, specific ion sensors and sensors for assessing spoilage (Smith, 1989). A description and real-time applications of these sensors will be the subject of future papers. Food Control - January 1990

CONTROL SYSTEMS FOR THE FOOD INDUSTRY The level of automation in the food industry varies considerably between companies, as well as between plants within the same company. Most food processing plants have evolved from small operations with a rather conservative, gradual approach to technological changes. In the food industry, automation began with the application of programmable controllers and singleboard computers on manufacturing equipment, and very simple control systems. These devices, particularly programmable controllers, were widely accepted by food processors because they were simple to operate and maintain. They were limited in what they could do: usually replace relays, timers and counters (Marien, 1988). Due to increased competition, however, the need for production flexibility, frequent changes in the manufacturing process and small engineering staffs, food processors can benefit from using flexible, easily configured control and process mangement systems. Today food processors have a choice of upgrading their programmable logic controllers (PLCs) or installing distributed control systems (DCS). They can build upon their existing PLCs (Marien,1988) to achieve fully integrated control systems performing various functions such as process control, raw material management, sales order processing, financial management and reporting. DCS-based architecture has performed these functions for large continuous processes. The DCS with all these benefits is now available small continuous and batch operations at a competitive price. The remainder of this paper describes the distributed control system and its advantages. DISTRIBUTED CONTROL SYSTEM (DCS) FOR THE FOOD INDUSTRY Distributed control systems have evolved significantly in the last ten years. From large systems tailored to the needs of continuous industries, such as refineries, DCSs can now respond to the requirements of small batch-oriented processes and can address a variety of automation projects. Many elements make up the subsystems of the DCS. Figure 2 shows a hardware configuration of the DCS. Localoperator station

AFil

\

iversol control network Process rnonoger

Logic monoger(option)

logic

----i

monogers -(option)

Figure 2

- -

Addition01 - - - process +- managers \ (option) \

Distributed control system hardware

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Automation

1

in the food industry: M. Dahm and A. Mathur

Level 3 Strategic ccntrol

Network communication Gotewoys

Production plonning Scheduling Multiplant optimization

Process monoger Application modules Operator interface

Modular botch automation Process model Set-point profiles Recipe monogement

Unit controller PLCS Event-bosed control Time-booed control

Composite variable sensors Process sens0rs Process octuotors

Process equipment

Figure 3

Control system hierarchy

The philosophy of distributed control is to break down a large application into smaller subsystems and bring the level of control down to the unit level when appropriate to decrease overall system response time. This makes it possible to exchange information between the different control units and allows for integrated decision making at the product line or plant level. The control of a process occurs at many different levels of logical and conceptual sophistication. There are many ways to categorize the control functions into different hierarchical levels. For purposes of discussion, a conceptual three-level structure is shown in Figure 3.

At the bottom of the system hierarchy, the input/ output devices, sensors, and actuators directly interact with the process. Regulatory control of process variables such as pressures and temperatures using proportional, integral and derivative (PID) control and logical operations such as time- and event-based control actions are carried out at this level. Individual controllers operate at the unit control level to control equipment such as blenders. To improve control at this level, several options are currently available to the users. For example, smart transmitters with some amount of data processing provide for closer monitoring of the process variables, automatic calibration, linearization; autotuners provide for automatic tuning of the PID controller constants as the process conditions change. In the near future, predictive controllers will be available as alternatives to PID controllers. Predicitive controllers will make the job of controller tuning very easy and intuitive. For example, instead of having to specify gains for the PID portions of the loop controller - quantities with no intuitive interpretation - the users would specify the settling time for the process or the desired rate of change of the controlled variable; the control actions necessary to achieve this will be computed by the predictive controllers. With these controllers, optimization at the local level will also be possible. The next level of hierarchy, labelled as the tactical level, improves control by integrating the control of independent process parameters. For example, if the product quality is out of specification, then set-point profiles or the recipe may have to be modified on-line. To perform on-line modification of set points or 34

recipes, a model of the process is required. The model can be a set of heuristic rules, a mathematical description of the process, or a combination of the two. DCS and other automation systems provide a user programming facility for such intelligent control of the process. For batch processes, vendors are currently offering preconfigured software modules. Users define the batch automation program by configuring and linking modules rather than by programming (Tolfo,1989). This feature is important because a process engineer or chemist can configure or modify the software without the support of a computer specialist (Spencer,l986). At the next higher level, communication networks for remote and local information exchange enable integration and coordination of the different subsytems. The distributed control system supports gateways to corporate computing systems, allowing management a real-time window into plant operation.

BENEFITS

OF THE

DCS

The distributed control systems provide the following benefits. Firstly, there are smaller logical blocks involving incremental programming and checkout, together with easy fault isolation and maintenance. A direct advantage of distributed control is to allow the software program to be broken down into smaller logical pieces, independent of system hardware. This makes system design more efficient and simple to modify. Software programs enable efficient recipe management, accurate recording and analysing of production data, and statistical process and quality control functions. Secondly, there is a graceful degradation from failure. The distributed nature of the overall system provides enough autonomy to the subparts so that massive failure of the system is unlikely. This is in contrast to a direct digital control strategy based on a single computer controlling the entire process. A third benefit is that islands of automation are removed via an integrated system. The distributed control systems enable communication across the different subunits of the manufacturing process, providing easy coordination of overall production rather than isolated islands of automation based on single controllers. A further benefit is from open architecture. Ease of integrating existing devices into the system, such as PLCs already present on the factory floor, is essential and requires that the selected DCS be able to communicate with devices from other vendors. Finally, there is the benefit from built-in information handling capability; involving information processing, data archiving, restart, and charting/trending. Distributed control systems offer the flexibility and expandability necessary in an industry undergoing rapid changes, as is currently the case in the food industry. Through its ease of implementation and operation, the distributed control system contributes significantly to the overall production optimization process, opening the doors to sophisticated tools for production planning and scheduling, quality control, multiline optimization, multiplant coordination, centralized and automated recordkeeping. Food Control - January 1990

Automation in the food industry: M. Dahm and A. Mathur

EXAMPLES OF DCS IMPLEMENTATION THE FOOD INDUSTRY

IN

One example is of an ice cream manufacturer looking to upgrade a processing plant from the existing level of automation based on isolated PLCs. The DCS solution provided the flexibility to run several products on the same line. The DCS also provided flexible sequencing of operations and reduced changeover time, thereby reducing overall production cost. Better monitoring of the process variables and statistical analysis of process trends resulted in improved quality control. Interactive graphics and displays gave plant personnel a better understanding of the process status in a timely fashion. The ability to secure the system using passwords added the benefit of production safety, which is essential in food manufacturing. Finally, the expandability of the system gave the manufacturer confidence that the selected automation strategy would remain applicable to production needs as the requirments for more sophisticated controls increased. A second example is the case of a dry packaged snack foods plant needing to upgrade its existing systems to integrate its process control and information management functions. DCS solution provided better monitoring and control of raw material handling, batch processing, forming, cooking, and packaging and warehousing operations were the main drivers for plant modernization. Even though the initial cost of a DCS solution was greater than a PLC-based system, the difference was paid back in improved functionality and productivity within four to six months. The solution also continued to reduce manufacturing costs and improve productivity at a faster rate than would the PLC-based solution.

CHECKLIST FOR AUTOMATION FOOD INDUSTRY A successful automation

IN THE

strategy hinges on:

(a) Defining a future vision of the company and its operations. (b) Developing alternative automation scenarios. (c) Defining criteria to evaluate each scenario such as:

Food Control - January 1990

need for production flexibility (multiple products on a single line, frequent recipe changeover); need for system expandability to meet increasing automation requirements in the future; requirements for open architecture (ability to integrate with existing equipment and/or with plant host computer); ease of operator and engineer interaction with the system; availability of support from vendor (training, application expertise, maintenance); range of advanced, proven technologies offered by the vendor (commitment to continuous evolution). Conducting a life-cycle cost study of competing alternatives. Defining a coordinated implementation plan.

REFERENCES Abdelrahan, M. (1988) Sensors and AI; the sixth sense. MeasurementS and Conrrol, 130, 146-147 CIuk, J.P. (1986) Automation Opportunities in Food Processing Plants. American Institute of Chemical Engineers Conference, Summer National Meeting, Boston, MA AIChE, New York, paper 52d Anon. Food sensors get in on the act. Sensor Rev. 9, 11-14 Mans, J. (1988) Sensors: Foods, 157 (3)

windows

into the process

Prepared

Marien, M (1988) Automation for success: a study of the food industry’s needs. ISATA 19th International Symposium on Automotive Technology and Automation, Vo1.2, Allied Automation, Croydon, UK, pp. 297-316 Opie, R. (1987) Biosensors set to make an impact Control Instrum. 19, 137-141 Paulus, K.O. (1987) Sensors and Measurement of Product Properties - Instrumentation and Process Control Bundersforchungsanstalt fuer Emaehrung, Karlsruhe FRG Smith, E. (1988) Sensors for food processing industry Proc. Sensors Expo September 13-15, Chicago, IL; Helmers Publishing, Peterborough, NH Smith, P. (1989) A sense for food, Sensor Rev. 9, 15-20 Talk, F. (1989) An introduction to modular Control Eng Sept Vol. II, 36 (9). 16-18

batch automation.

Received 10 October 1989 Revised 23 October 1989 Accepted 2 November 1989

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