Embedded Control and Monitoring Systems in Production Machine Networks

10th International Symposium on Process Systems Engineering - PSE2009 Rita Maria de Brito Alves, Claudio Augusto Oller do Nascimento and Evaristo Chalbaud Biscaia Jr. (Editors) © 2009 Published by Elsevier B.V.

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Embedded Control and Monitoring Systems in Production Machine Networks Sirkka-Liisa Jämsä-Jounela,a Mikko Huovinen b a

HelsinkiUniversity of Technology, Department of Biotechnology and Chemical Technology, P.O.Box 6100, FI-02015 Espoo, Finland b Tampere University of Technology, Department of Automation Science and Technology, P.O.Box 692, FI-33101 Tampere, Finland

Abstract The ongoing globalization trend is tightening competition and setting new, higher efficiency requirements in the process industries. In order to enhance the efficiency of the production chain, new functionalities and information networking must be incorporated into the production equipment. This paper proposes a concept of equipment automation that utilizes new information and communication technologies and more flexibly adds equipment intelligence. The feasibility and applicability of the concept is demonstrated via case studies of a grinding circuit and a pulp drying process. Keywords: Networked equipment automation, intelligent process equipment.

1. Introduction The globalization process is tightening competition and setting, higher efficiency requirements in the process industries. In addition, factories now have to be considered as a part of sustainable development. Energy savings and pollution prevention have become priorities. Safety and maintenance are also listed as the main equipment design parameters. At the present time, however, the intelligence level of the process equipment and their networks is still low. In order to enhance the efficiency of the production chain, new functionalities and information networking must be incorporated into the production equipment. This can be further enhanced by applying embedded automation middleware to manage complex networked machines and distributed resources. The goal of automation middleware is to increase the intelligence level of the production machines by networking and integrating the embedded systems of the machines into larger automation system entities. The functionalities embedded in the middleware cover the management of the whole process system at the life-cycle scale. The methods can utilize connections to higher-level systems and remote resources, as well as to the information-refining tools provided by the middleware platform. The middleware thus integrates lower level process resources, and further refines the collected information into a more convenient form that is subsequently presented to the users and/or to other information systems, such as MES or ERP. The purpose of this paper is to propose a common way of incorporating the current communication technologies, and especially the communication protocol and network topology design, into process equipment in such a way that it facilitates the implementation of new methods and subsequently satisfies the efficiency requirements.

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2. Survey of Industrial Automation Architecture and Communication Technologies The evolution of communication technologies has had a strong influence on changes in the structure of industrial automation systems. Up until now, communication support in plant automation systems has been defined according to the Computer Integrated Manufacturing (CIM) concept. In this hierarchical structure, levels of functionality are identified in such a way that each device is designed for a specific task, and specific networks are used to interconnect devices at the same level, i.e. running the same task. However, the devices have recently started to include more than one function, or module, which increases the intelligence level of the equipment automation. Devices like sensors that have traditionally been used for measurement now have to support e.g. maintenance or monitoring tasks. This means that the traditional hierarchical structure is increasingly being replaced by a distributed communication architecture. Nevertheless, the hierarchical structure still exists - and this is also advisable - in most of the process control strategies and plant automation systems, as illustrated in Fig. 1 and 2. This phase in the evolution of automation systems has been called FCS (Field Control System).

Fig. 1. Hierarchy of the plant automation.

Fig. 2. Future scenario of the plant automation

2.1 Low-layer communication protocols Currently the most widely available industrial networks can be classified into three main categories: traditional fieldbusses, Ethernet-based networks and wireless networks. A comparison of the key properties of the currently, most widely available networks in each of the three main categories is given in Table 1. 2.2 High-layer data specifications The information standards for process operation and maintenance are driven by OpenO&M Initiative joint working groups, which mainly represent three industrial organizations: MIMOSA, the OPC Foundation, and ISA's SP95. One of the most strongly established standards, the OPC, also enables the use of state-of-the-art technologies such as web services. On the other hand, the traditional fieldbusses (like Profibus or Foundation Fieldbus) have defined concepts for the manufacturerindependent integration of field devices such as FDT/DTM.

3. Proposed Architecture for the Networked Equipment Automation 3.1 Components of the automation concept The concept of equipment automation must be applicable over a wide range of different industrial processes. The main starting point is to bring the automation, with intelligent software-based functionalities, near to the process equipment while, on the other hand,

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designing a communication network that robustly provides the services that are already incorporated. Therefore, the automation devices for one specific piece of equipment or sub-process are networked into one process system node, thereby providing connectivity to other parts of the process. The equipment ‘intelligence’ is embedded as a part of the automation devices, using software-based modules (Fig.3.) Switch

Device

Device

Device …

M M M M … MM … M … M M

Process system node: a set of networked devices related to a certain process equipment. Devices: process specific automation component categories. Modules: containing the intelligent, software based functionalities in the devices.

Fig. 3. Structure of the process system node.

The process system nodes are further connected to the supervisory automation level with a high bandwidth network (Fig. 4). In addition, the nodes can also provide a wireless connection link. Finally, in order to implement the equipment’s advanced operating algorithms and procedures, a data processing unit (PLC or soft-PLC) is needed as a part of the process system node. This leads to a scheme in which the equipment automation provides the intelligent operating functionalities related to a specific task, which typically means one unit operation in the process chain. Compared to the traditional DCS hierarchy, the addition of intelligence offers a more dynamic platform for autonomous systems. Intelligent devices can act more independently and the improved communications enable interaction between the distributed assets. In fact, the FCS hierarchy provides a new platform for the implementation of agent technologies in the process industry. 3.1. Communication network topology The architecture of the concept relies on a backbone that is capable of providing the main connectivity between the different devices. Moreover, it includes the connection point to remote resources via the Internet. The process system nodes, which are linked to the backbone, form sub-networks. These provide supplementary networks for establishing the instrumentation power supply and wireless links. It also manages the mutual interconnections between local devices. Redundancy is also provided for the backbone. The network system topology is presented in Fig. 5. The communication protocol applied in the backbone should be able to link with office and remote resources and, as a result, have the same low layer technology as used in Internet networks, to provide a large bandwidth to integrate all the sub-networks, and also to support several high layer technologies, such as web and multimedia applications. The use of Ethernet networks is therefore proposed. The Ethernet technology is applied in the process system node network level. The connection to the devices is shared by using switch in order to improve the time determinism and isolate the local traffic. The Ethernet also has the advantage of facile connectivity to traditional fieldbusses. Additionally, Ethernet ensures device interoperability by supporting open standards, such as OPC.

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PLANT AUTOMATION SYSTEM Sensors Computing Control Communication

Process system nodes

EMBEDDED PROCESS EQUIPMENT AUTOMATION

Switch

Switch

Hub

MATERIAL FLOW

Hub

DB HMI Sensors / Actuators

Sensors / Actuators Wireless Link

PLC / PC

Hub

DB HMI

DB HMI

Wireless Link

Fieldbus

Sensors / Actuators Wireless Link

Fieldbus

Sensors / Actuators

Sensors / Actuators

Fieldbus

Sensors / Actuators

UNIT OPERATION

UNIT OPERATION

UNIT OPERATION

Sub-process / Process circuit

Switch

PLC / PC

PLC / PC

Embedded intelligent functionalities

UNIT OPERATION

Fig. 4. Concept of the equipment automation level between the physical process and the supervisory plant automation system. Remote Connections

Switch & Firewall Office Ethernet Plant Automation System

Router HMI

PLC

DB

EW Industrial Ethernet

Redundant Links

Switch

Switch

PLC / PC

Hub

DB HMI

Switch

PLC / PC

Hub

DB HMI

Analyzers

Hub

Sensors / Actuators Wireless Link

Fieldbus

Sensors / Actuators

PLC / PC DB HMI

Sensors / Actuators Wireless Link

Switch

Sensors / Actuators Wireless Link

Fieldbus

Sensors / Actuators

Wireless Link

Fieldbus

Sensors / Actuators

Fig. 5. Topology of the equipment automation network architecture. Table 1. Comparison of the currently, most widely available industrial networks T yp e

P ro to c o l

M a n u fa ctu r e r

Throug hput

CAN

B o sch

10k b /s - 1 M b /s

W o rld F IP( 11 58- 2) Sc hn e i de r

P ro fib us D P

Traditional Fieldbus

P ro fib us P A

T yp e

D e vice N e t C o n t ro lN et In t er bu s

Ethernet Based Wireless

C yc le T im e

2 m s, 5 m s

R an g e (L e n g th )

N u m b e r o f D ev ice s

40 m ( 1M b /s ), 5km ( 10k b /s)

m a x. 3 2

1k m ( 1M b /s ), m ax 4k m

m a x. 2 5 6 , 64 / s eg

d e p en d in g o n 10 0 m (1 2M b /s) , 9,6kb /s - 12M b /s c o n f ig u rat io n 1,2k m (9 ,6k b /s ) < 2m s d e p en d in g o n Sie m e n s 31,25 kb /s c o n f ig u rat io n 19 0 0m < 2m s 2 , 0 m s , 4 ,2 m s, 10 ms 5k m ( 5M b /s ), R o ckw e ll 5M b /s < 0 .5 m s 30 k m + o p tica l A u to m at io n f ib er) 1 , 8 m s , 7 ,4 m s, Ph o en ix C on t ac t 500 k b/s ~1 3km 14 0 m s Sie m e n s

E n erg y E ffic ien c y

P o we r o ve r n e tw o r k s olu t io n

m a x. 1 2 6

m a x. 3 2 /se g

P o we r o ve r n e tw o r k s olu t io n

m a x. 9 9 m a x. 5 1 2 P o we r o ve r n e tw o r k s olu t io n P o we r o ve r n e tw o r k s olu t io n

A S -i

Sie m e n s

167 k b/s

4, 7 m s

10 0 m /seg , 30 0m

m a x. 6 4

F o u n d ati on F ie ld bu s H 1

F ie ld b u s F o un d at io n

31.25 kb /s

3 6 m s ,10 0 m s , 60 0 m s

m ax 1 900 m

m a x. 3 2

P ro to c o l

M a n u fa ctu r e r

Throug hput

C yc le T im e

R an g e (L e n g th )

N u m b e r o f D ev ice s

E n erg y E ffic ien c y

1 0M b /s, 10 0M b /s, 1 G b /s

> 10 m s

F o u n d atio n F ie ld b u s H S E

R o ck w ell Au to m at io n F ield b u s F o u n d a tio n

E th e rC at

B ec kh o ff

1 00 M b /s

< 50 μ s

10 0m /se g

~ 6 553 5

P o w er o v er n et wo rk s o lu tio n

P o w erlin k

B&R

1 00 M b /s

< 50 0 μ s

10 0m /se g

P ro fiN e t IO S erc o n III

Sie m en s B o sc h R ex ro th

1 00 M b /s 1 00 M b /s

1 m s , 1 0m s 3 1,5 μ s

10 0m /se g 10 0m /se g

M odbus TCP

Sc h n e id er

1 0M b /s, 10 0M b /s, 1 G b /s

> 10 m s

P ro to c ol

M an u fa ct ur e r

Th r ou gh p ut

C y c le T i m e

E th e rn et/IP

T yp e

31,25 kb /s, 1M b /s, 2,5M b/ s (5 M b /s o p t ical fib e r )

IE EE 80 2.1 1 (b /g /n ) B lu e to o th , IE EE 8 02 .15 .1 IE EE 80 2.1 5.4 /Z ig B e e W ireles sH a rt

H art C o m m u n ica tio n F o u n d a tio n

1 00 M b /s

10 0m /se g

R a ng e (L e ng th )

m a x. 25 4

Nu m b er of D ev i c e s

P ow e r C on s um p ti on

5 4M b /s, 10 0M b /s

30 -10 0m

1 M b /s

10 m

7

Low

2 0k b /s, 40 kb /s , 2 50 kb /s

10 m

~ 6 5k

V ery L o w

2 50 kb /s

10 m

M ed iu m

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4. Add–On Service Modules of the Intelligent Process Equipment Intelligent process equipment in modern automation systems can also be thought of as forming a functional hierarchy. The equipment provides services designed to meet the higher level objectives. There are production management services consisting of daily operations, abnormal event management, operator support and training, product data and lifecycle management services. All these consist of lower level activities, such as process control, performance monitoring and field management. The implementation of the activities consists of tools and routines as presented in Fig. 6. INTELLIGENT PROCESS EQUIPMENT

SUSTAINABLE DEVELOPMENT -RAW MATERIALS -ENERGY -ENVIRONMENT

OPERATION - PRODUCTION STRATEGY - EFFICIENCY - QUALITY

SAFETY

MAINTENANCE

Objectives

PRODUCTION MANAGEMENT

ABNORMAL EVENT MANAGEMENT

OPERATOR SUPPORT AND TRAINING

PRODUCT DATA MANAGEMENT

LIFECYCLE MANAGEMENT

Services

PROCESS OPTIMIZATION

PROCESS CONTROL

FAULT TOLERANT CONTROL

SIMULATION

PROCESS PERFORMANCE MONITORING

FIELD MANAGEMENT

Activities

MODELING

DATA LOGGING

DATA PROCESSING

COMMUNICATION

Tools and routines

Fig. 6. Functional hierarchy of the intelligent process equipment

5. Case Examples 5.1. Case example: applying the concept of equipment automation to a grinding circuit The proposed equipment automation concept is applied to an example of a mineral grinding process. It is proposed that the instrumentation of the process is grouped into four categories, typical for the process. These are: basic sensors, machine vision, process analyzers, and data processing units. The process system nodes are divided according to the data processing units for the operation and monitoring of the mill, pump and hydrocyclone. The fourth node is reserved for an elemental analyzer, which is located physically further from the grinding circuit. One of the most important nodes, which includes the ‘mill automation’ data processing unit, has a wireless link enabling connection to the particle size and elemental assay analyzers. Other wireless sensors located in problematic points, such as the rotating mill shell, can also be added to the system. The industrial Ethernet connection is favored for all the instrumentation connections, as illustrated with the ‘machine vision’ device in the figure. The network topology of the equipment automation in this case is illustrated in Fig. 7. 5.2. Case example: applying the concept to monitor a pulp drying process The concept was also implemented and deployed in the drying section of a Finnish pulp mill. The application is primarily intended to be used for production management services through process optimization and performance monitoring tools. It is also useful for abnormal event management, lifecycle management and operator support. The tools available for process optimization and performance monitoring include clustering, conditional histogram and control loop monitoring. An extensive performance measurement system has also been developed. The measurement system is hierarchical representing the whole system, subprocesses, control loops and the

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equipment. On the equipment level features of intelligent field devices were exploited while on the control loop level a control loop monitoring tool called LoopBrowser was used. Examples of subprocess measurements are relative energy consumption and relative variations of controlled variables. The whole drying process was represented by an OEE indicator. Remote Connections

Switch & Firewall Office Ethernet

Router

Plant Automation System Industrial Ethernet

Node: Mill Automation

Wireless Link

Node: Cyclone Automation

Node: Pump Automation

Node: Analyzer

Machine Vision Wireless Link Analyzer Wireless Link

Wireless Sensors

Sensors / Actuators

Sensors / Actuators

Sensors

Sensors

Mobile HMI

Fig. 7. Simplified abstraction of the network topology, with device connections for the process. The clustering method is based on a modified K-means algorithm for identifying operating points and for detecting abnormal situations. The algorithm was chosen based on its computational simplicity enabling easy online implementation. The information is also used for diagnostic purposes because the application provides a contribution plot for showing the deviations of the input variables from their typical values. The conditional histogram method is used for constructing a database representing normal performance in each operating point. The method also includes routines for detecting whether the current measured performance deviates from the normal performance. The control loop monitoring system produces data about the performance of the monitored control loops. Four performance indices are used, which basically measure the accuracy and stability of the control loops.

The refined information serves the lifecycle module by providing monitoring performance throughout the equipment lifecycle. Intelligent field devices can be incorporated to deepen the scope of the application through embedded device level monitoring, as well as diagnostics which provide valuable information about the performance and ambient conditions of the field devices. For example, valve positioners typically provide control error and stiction measurements that can be used for determining whether a detected abnormal situation originates from the monitored valveactuator-positioner package or from an outside source. Efficient exploitation of field device level information requires the use of device integration technologies, such as FDT/DTM. The overall performance measurement system was designed to give a comprehensive picture of the overall state of the whole process through the use of subprocess performance indicators. These measure e.g. relative variations in the controlled variable and efficiency measures.

6. Conclusions In order to meet the tightening performance requirements in the process industries, the efficiency of the process equipment must be improved. Therefore, an equipment automation concept was formulated and proposed The concept outlines the procedure for efficient utilization of the latest information and communication technologies.