Cyber-virtual Systems

Simulation, Validation & Visualization

Jan Olaf Blech, Maria Spichkova, Ian Peake and Heinz Schmidt

RMIT University, Melbourne, Australia

Keywords:

Cyber-physical Systems, Virtual Interoperability Testing, Simulation, System Modeling, Formal Speciﬁca-

tion, Visualization.

Abstract:

We describe our ongoing work and view on simulation, validation and visualization of cyber-physical systems

in industrial automation during development, operation and maintenance. System models may represent an

existing physical part – for example an existing robot installation – and a software simulated part – for example

a possible future extension. We call such systems cyber-virtual systems. In this paper, we present the existing

VITELab infrastructure for visualization tasks in industrial automation. The new methodology for simulation

and validation motivated in this paper integrates this infrastructure. We are targeting scenarios, where indus-

trial sites which may be in remote locations are modeled and visualized from different sites anywhere in the

world. Complementing the visualization work, here, we are also concentrating on software modeling chal-

lenges related to cyber-virtual systems and simulation, testing, validation and veriﬁcation techniques for them.

Software models of industrial sites require behavioural models of the components of the industrial sites such

as models for tools, robots, workpieces and other machinery as well as communication and sensor facilities.

Furthermore, collaboration between sites is an important goal of our work.

1 INTRODUCTION

Operation, development, maintenance (including

modiﬁcations and extensions) of industrial automa-

tion facilities like factories or mining sites proﬁt from

software support such as software based monitoring,

controlling and collaboration tools. This requires

visualization capacities as well as software models

of the physical entities involved and ways to reason

about them.

Industrial automation facilities typically comprise

machinery like robots and their components. Compo-

nents may serve as actuators: tools, conveyor belts,

work pieces or pipes, valves and pumps in cases were

ﬂuids or gases are processed. Sensors can be found

throughout industrial automation sites. The data

gathered from the sensors may be stored in a central

facility.

Hardware-in-the-loop (HIL) approaches

(Schlager, 2008) are now standard in the devel-

opment of system components in domains such as

automative systems, e.g., (Isermann et al., 1999),

avionics and also in industrial automation. In HIL,

parts of a system are simulated in software to test

a distinct system component. In this paper, we are

going one step further and aim at simulating different

parts of an industrial site. We do not restrict our ap-

proach to the development, but also aim at supporting

operation and maintenance of industrial automation

facilities. Furthermore, we aim at visualizing remote

facilities or parts of them. This is especially crucial

when developing, operating or maintaining industrial

sites located in areas that are difﬁcult to access such

as mines and oil rigs and for collaboration between

different sites and sharing knowledge between them.

In the case where components of a system are

manufactured at different places, transport from

component development and production locations to

integration and deployment sites can signiﬁcantly

increase the whole development costs as well as

time. Integration can reveal additional work tasks

and further transportation of the system’s parts may

be necessary. If a system’s components are bulky

or heavy, this may also delay optimization and

correction.

For this reason, we present an existing visual-

ization infrastructure - the Virtual Interoperability

Test Lab (VITELab)

. a global laboratory connecting

VITELab is an eResearch facility of the Australia-

India Research Centre for Automation Software Engi-

neering (AICAUSE), a partnership between RMIT Uni-

218

Olaf Blech J., Spichkova M., Peake I. and Schmidt H..

Cyber-virtual Systems - Simulation, Validation & Visualization.

DOI: 10.5220/0004952402180225

In Proceedings of the 9th International Conference on Evaluation of Novel Approaches to Software Engineering (ENASE-2014), pages 218-225

ISBN: 978-989-758-030-7

 2014 SCITEPRESS (Science and Technology Publications, Lda.)

industry and university sites and providing a collab-

oration platform for experimental design and testing

of cyber-physical systems. Among its aims are to

reduce development costs by simulating and virtually

testing possible deployments before the system is

actually physically set up.

We also present the corresponding new and

ongoing research directions towards combining vi-

sualization and software support for reasoning about

industrial automation facilities. The ideas featured in

this paper comprise the following ingredients:

• The use of VITELab, in particular the Global Op-

erations Visualization (GOV) Lab, a high resolu-

tion multi-screen visualization facility.

• Software models for system components that

comprise spatio-temporal information about a

component’s behavior and ways to reason about

them, testing and simulation.

• The combination and integration of these for in-

dustrial automation.

Our work is a step towards software solutions facili-

tating global collaboration between developers, oper-

ators and maintenance of industrial sites.

2 RELATED WORK

Modelling Aspects. Different languages exist for

the modeling of embedded and automation systems.

Standards like IEC 61131-3 and IEC 61499 tar-

get the software part of control systems and thus

specify the behavior of machinery. In the scien-

tiﬁc community different modeling languages such

as the Petri-Net semantics based BIP (Basu et al.,

2006) for distributed asynchronous systems and Mod-

elica, providing means for modeling and simula-

tion of systems have been established, cf. (Do-

nath et al., 2008), (Fritzson, 2004), (Anderson and

Fritzson, 2013). Modelica is object-oriented and

its latest extensions allow modelling of system re-

quirements (Tundis et al., 2013) as well as simu-

lation of technical and physical systems (Fritzson,

2011). Modeling theories for distributed hybrid sys-

tem such as SHIFT (Deshpande et al., 1997) and R-

Charon (Kratz et al., 2006) guarantee a complete sim-

ulation and compilation of the models, but do not sup-

port veriﬁcation or analysis of the system on the mod-

eling level. Same limitations also apply to the input

language of the model checkers UPPAAL (Behrmann

versity and the ABB Group (Australia and India),

http://rmit.edu.au/research/aicause

et al., 2004) and PHAVer (Beek et al., 2006): the ver-

iﬁcation capabilities do not match the whole expres-

siveness of the modeling languages.

Assigning semantics to logical entities for catego-

rizing and reasoning about them is a one goal of our

models for industrial automation facilities. The con-

cept has been made popular in the context of the se-

mantic web (Berners-Lee et al., 2001) and ontologies

(Staab et al., 2001).

Spatial Aspects. The modeling of industrial au-

tomation sites involves spatial aspects. For example,

robots must ensure a behavior that guarantees col-

lision avoidance and the correct handling of work-

pieces. Systems that comprising thermal aspects like

heat exchangers need adequate models to cover their

behavior. SpaceEx (Frehse et al., 2011) allows the

modeling of continuos hybrid systems based on hy-

brid automata. It can be used for computing over-

approximations of the space occupied by objects. A

process algebra for 3D objects is provided in (Cardelli

and Gardner, 2010). Results on spatial interpreta-

tions are explained in (Hirschkoff et al., 2003). A

quantiﬁer-free rational fragment of logic suitable for

describing spatial scenarios has been shown to be

decidable in (Dal Zilio et al., 2004). Logics for

spatio-temporal reasoning go back to the seventies.

The Region Connection Calculus (RCC) (Bennett

et al., 2002) includes spatial predicates of separation.

RCC features predicates indicating that regions do not

share points at all, points on the boundary of regions

are shared, internal contact where one region is in-

cluded and touches on the boundary of another from

the inside, overlap of regions, and inclusion.

Cyber-physical Aspects. Many approaches on

mechatronic/cyber-physical systems omit an abstract

logical level of the system representation and lose

the advantages of the abstract representation. The

work presented in (Vogel-Heuser et al., 2011) de-

ﬁnes an extensive support to the components com-

munication and time requirements, while the model

discussed in (Hadlich et al., 2011) proposes a com-

plete model of the processes with communication.

In traditional development of embedded systems e.g.,

(Berger, 2002), the system is usually separated into

software and hardware parts as soon as possible, at

an early stage of the development process. This does

not always beneﬁt the development process, because

when using an abstract level of modeling the differ-

ence in the nature of components does not necessar-

ily play an important role. (Sapienza et al., 2012)

and (Spichkova and Campetelli, 2012) independently

suggest to use a platform-independent design in the

early stages of system development. The approach

presented in (Sapienza et al., 2012) introduces the

Cyber-virtualSystems-Simulation,Validation&Visualization

219

idea of pushing hardware- and software-dependent

design as late as possible, however, the question of the

current practical and fundamental limitations of log-

ical modeling in comparison to cyber-physical test-

ing, is not completely answered. In comparison to

(Sapienza et al., 2012), the focus of (Spichkova and

Campetelli, 2012) is on reutilisation and generalisa-

tion of two existing software systems development

methodologies (both elaborated according to the re-

sults of the case studies motivated and supported by

DENSO Corporation and Robert Bosch GmbH) for

application within the cyber-physical domain to bene-

ﬁt from the advantages these techniques have shown.

The question, how deep we can go on the modeling

of cyber-physical systems on the logical level is still

open in both approaches. The goals presented here

are also related to hybrid commissioning (Dominka

et al., 2007).

Early Analysis Aspects. The idea of early anal-

ysis of critical system faults has the goal to identify

faults which mutate the safety critical behaviour of

the system, and to identify test scenarios which can

expose such faults from an abstract modeling level,

i.e. by generation of tests (both for real system and its

model) from formal speciﬁcations or from the CASE

tool models (cf., e.g., (Hazra et al., 2013; Broy et al.,

2005; Pretschner and Philipps, 2005)). The approach

has certain limitations due the abstract nature of the

formal model serving as a base for the test generation

as well as an underlying assumption of existence of a

precise formal model of the system being developed.

Even when taking into account these limitations and

assumptions, these approaches allow automatization

of test case design and make the design process more

stringent. VITELab and the described research com-

plements commercially available visualization soft-

ware for collaboration purposes in industrial automa-

tion such as DELMIA

. The approach described here,

is building on (semi-)formal models which carry se-

mantic meaning and are suitable for automatic inter-

pretation and processing, whereas the DELMIA focus

is even more on visualization.

3 FROM CYBER-PHYSICAL TO

CYBER-VIRTUAL SYSTEMS

Let us discuss an example scenario based on the ideas

of the virtual interoperation testing. In an indus-

trial plant we require the integration/interoperability

of n + 1 bulky/heavy robots (cf. Figure 1): a robot of

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the type AType (lets call it robot A) is assembled in

location L

, the n other robots are of a different type

BType and are assembled in a different location lo-

cation L

. The robots are in different locations and

making them work together in a different shared de-

ployment location requires extensive simulation, test-

ing and collaboration.

Assuming in addition that the n robots of type

BType perform simultaneously similar movements

and actions (e.g., they stamp similar details on work-

pieces on a conveyor belt and are doing the same

movements, even in the case their stamps are differ-

ent), we can simulate their behaviour using a single

robot B: its actuator information will be replicated

to obtain n virtual models B

, . . . , B

, and its sensor

information will be extended by the composition of

the modeled sensor information from B

, . . . , B

. The

sensor information of the robot A will be a composi-

tion of the real sensor data and the sensor data mod-

eled according to the actions of B

, . . . , B

Thus, to check the interoperability of the robot A

and n robots of the type BType on the level of virtual

interoperability testing, we need only two real robots:

a robot A and a robot B. Moreover, they could be lo-

cated in L

and L

respectively, because the simulator

and visualization facility may take the role of a physi-

cal medium between them, allowing to ignore the real

distance between robots and also allowing to have a

visualisation of the test and simulation not only at L

and L

, but also on the third place L

, where the cor-

responding laboratory is located.

General ideas for using the virtual interoperabil-

ity test lab (VITELab) for the use of remote cyber-

physical integration/interoperability testing in a vir-

tual environment as a middle step between an ab-

stract modelling and real testing were presented in

(Spichkova et al., 2013a). Figure 2 shows the VITE-

Lab facility in operation, viewed from the GOV Lab.

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Figure 2: VITElab in operation.

VITELab gives a platform for a new level of simula-

tion and integration: interoperability simulation and

testing is performed early and remotely, for exam-

ple while cyber-physical components are in the pro-

totyping stage i.e. on the workbench: individual com-

ponents (e.g., robots, manufacturing cells), are con-

nected in a suitable virtual environment, without be-

ing deployed at the same place physically. Successful

testing and simulation could signiﬁcantly reduce the

well-documented costs arising from discovery of de-

sign faults after implementation.

Research connected to VITElab is inﬂuenced by

larger cooperations in the industrial automation do-

main. Remote integration and testing allows for an

integration and testing phase of a real system assum-

ing a certain level of abstraction where the network,

the virtual environment and the remote embodiments

may be abstractions themselves. This level of abstrac-

tion includes real physical components of the system

(in the case of the VITElab project, e.g., real robots

and production plants) and more characteristics of the

network, environment and embodiments. Our models

and their visualization can give us the possibility to

identify (i) a number of problems and inconsistencies

on the early stage of system development and verify

especially important system’s properties before the

real system is build and integrated, and (ii) possible

weak points in the system (such as some timing prop-

erties, feature interactions, component dependancies)

which we should focus on, during the testing phase.

4 RESEARCH CHALLENGES

AND CORRESPONDING

PROJECTS

This section presents research challenges connected

to cyber-virtual systems, VITELab, simulation and

validation in more detail.

Main Directions for Research. We have identiﬁed

the following research challenges in our scenario:

• Simulation and the visualization of simulation

runs.

• Testing, veriﬁcation and validation of cyber-

virtual scenarios.

• Gaining expertise and knowledge from joint work

using visualization and simulation.

• Sharing and making expertise and knowledge

available for similar development projects and for

related operation and maintenance tasks in related

facilities.

Software Models for Industrial Plants. In our

work, we propose two ingredients related to software

models for addressing these challenges:

• (Semi-)formal descriptions based on human

factors approaches to achieve better readabil-

ity/usability and understandability.

• Spatial behavioral models that capture the charac-

teristics of entities and components in industrial

automation. We are interested in establishing a

type system for these components.

Existing VITELab Projects. The research chal-

lenges identiﬁed in the context of VITELab fall into

the network, cloud and distributed computing areas,

and are covered by the following ongoing projects:

• Network connectivity between sites with special-

ist equipment is supported by dedicated links and

research software stacks.

• The Cyber-physical Simulation Rack (CSRack),

is a multi-node cloud server rack with attached

RAID storage provides parallel cloud computing

capability to support modeling and simulation and

the capability to act as a ’cloudlet’ gateway to ma-

jor national and international cloud facilities such

as NeCTAR

• The Global Operations Visualization (GOV) Lab

project, provides videoconference and streaming

capability to remote sites combined with a large

high resolution tiled display wall.

• The Advanced Manufacturing Robot Interopera-

tion Test (AMRIT) lab provides industrial robots

connected to the GOV lab. The robots com-

prise arms, sensors and cameras as “eyes on the

robots”.

National eResearch Collaboration Tools and Resources

Project, https://www.nectar.org.au

Cyber-virtualSystems-Simulation,Validation&Visualization

221

sensors

actuators

sensors

actuators

physical

world

software simulation

Figure 3: Robot in the loop.

Further research challenges exist in the connection

of software based development tools for industrial

automation systems to the described infrastructure.

Such tools may need to undergo a redesign of the

software architecture to enable this, cf. (Peake et al.,

2013).

5 FROM (SEMI-)FORMAL

METHODS TO

VISUALIZATION &

VALIDATION

A starting point for our work is a HIL approach and

is depicted in Figure 3. Here, the interplay of a physi-

cal robot with a virtual simulated robot is shown. The

actions of the physical robot to the environment are

observed passed to the robot simulation and reacting

actions are calculated. These actions are (by)passed to

the sensors of the physical robot to simulate the inter-

play. The interplay can be analyzed both by software

tools as well as human inspection. The human based

analysis proﬁts from visualisation capabilities for the

display of the simulated robot and the monitoring of

the physical counterpart.

Human Factors and Formal Models. To enable

simulations we need (semi-)formal descriptions of

robot behavior, which should not only ﬁt for the

simulation purposes but also be readable for sys-

tem/veriﬁcation engineers. In our approach we follow

the ideas based on human factor analysis within for-

mal methods (Spichkova, 2013a; Spichkova, 2012).

This allows to have short and readable speciﬁcations

of component behavior. It is appropriate for switching

between different modeling, speciﬁcation and pro-

gramming languages and is suitable for the applica-

tion of speciﬁcation, reasoning and proof methodol-

ogy (Spichkova et al., 2013b; Spichkova, 2007).

Formal Proofs and Veriﬁcation. In the case of for-

mal proofs, one of the main points of this method-

ology is an alignment of the future proofs during

the speciﬁcation phase to make the proofs simpler

and appropriate for application in practice. One di-

rection for reasoning about a system represented in

a formal speciﬁcation framework, is the veriﬁcation

of its properties by translating the speciﬁcation to a

Higher-Order Logic and subsequently using the theo-

rem prover following (Spichkova, 2013b).

Spatial Behavioral Types. Our (semi-)formal

models comprise spatial behavioural. This can be

assigned to both physical and virtual simulated

robots, their components and other entities interact-

ing with them as shown in Figure 4. Following the

ideas presented in (Blech et al., 2012) these spatial

behavioural models can serve as a type system similar

to types systems in higher programming languages

like C and Java which come with basic types like

integers, Strings and ﬂoating point values as well as

composed types like records or classes. Here, we

regard (spatial) Behavioural Types (BT). BT act as

types for virtual or physical entities in our automation

scenarios. They are characterised by the following

core concepts:

• Abstraction. BT represent aspects of robots, robot

components and other entities in industrial au-

tomation. BT abstract from details concerning in-

teractions and internal structure.

• Conformance. Type conformance of BT is used to

relate entities in industrial automation correctly to

a BT.

• Reﬁnement. BT should comprise a notion of

spatio-behavioral reﬁnement that allows replac-

ing a component by a reﬁned one. For example,

the concept of reﬁnement shall allow replacing a

robot by a newer version that essentially provides

the same functionality plus some new features.

• Compatibility. Compatibility checking of BT is

used to decide whether a component does indeed

match required needs based on provided and ex-

pected BT. It should be decidable and automatic.

• Inference. A BT framework should allow to infer

composed BT. For example, the BT of a robot may

be inferred from the BT of its components.

Spatial Behavioural Types for Simulation and Val-

idation. BT can serve as a speciﬁcation basis for

the components of robots and the robots composed

of them. BT can be used to build models of industrial

automation facilities. Using BT based speciﬁcations,

we can perform:

• Simulation and visualization for human inspec-

tion and collaboration between developers, opera-

tors and maintenance personnel.

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R1 R2 R3 R4 R5

existing robot existing robot

existing robot

simulated robot

BT BT BT BT

composition

analysis

simulation

veriﬁcation

validation

conveyor belt

visualization

Figure 4: Combining virtual and physical robots with BT.

• Automatic spatio-temporal reasoning for collision

detection of robots and other entities.

• Checking automatically the required sensor

ranges and regions affected by physical entities.

• Guaranteeing correct interplay of tools and work-

pieces in time and space.

• Simulating the replacement of an entity such as a

robot arm by another (reﬁned) version.

• Documenting behavior of system installations and

sharing this for collaboration.

The BT concept is following the idea of interface au-

tomata (de Alfaro and Henzinger, 2001). It has been

proposed as a type system for OSGi systems in the

past (Blech et al., 2012). Theorem prover export

and interactive veriﬁcation of properties were stud-

ied in (Blech and Sch

atz, 2012) and may be an issue

for future work together with human-factor analysis.

Checking compatibility and means to make behav-

ioral system descriptions compatible were examined

in (Blech, 2013). For checking the spatio-temporal

properties in our scenarios we incorporate the Be-

SpaceD (Blech and Schmidt, 2013) tool. Checks

in BeSpaceD are done by converting spatio-temporal

models or BT and required properties into SMT and

SAT problems and applying suitable solving tech-

niques such as the z3 SMT solver (De Moura and

Bjørner, 2008).

6 CONCLUSIONS

The presented research is ongoing work and part

of larger cooperations with an industrial automation

company. In this paper, we presented an overview

on the existing VITELab infrastructure facilitating re-

mote collaboration by large screen/multi screen vi-

sualization. The aim of this infrastructure is to re-

duce the development costs by simulating and virtu-

ally testing possible deployments before the system is

actually physically set up. We have highlighted con-

nected research questions, as well as explained the

VITELab applications in operating, developing and

maintaining industrial automation facilities. The con-

nection to spatial behavioral models and a related type

system for the simulation of industrial automation fa-

cilities and the connection to visualization capacities

was presented in more detail.

ACKNOWLEDGEMENTS

We would like to thank staff from RMIT ITS, Proper-

tyServices, eResearch and the VITELab team, in par-

ticular Lasith Fernando, Ravi Sreenivasamurthy and

Garry Keltie.

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