Enhancing Industrial Information Exchange in Service Architectures

and Collaborative Business Processes

Petri Kannisto

Department of Automation Science and Engineering, Tampere University of Technology,

P.O. Box 692, 33101 Tampere, Finland

Keywords: Industrial Information Systems, Service Architecture, Integration, Business Collaboration.

Abstract: This paper presents the challenges and shortcomings of the current utilities and practices for industrial

information exchange and collaborative business processes. While several enabling technologies exist, the

data exchange between industrial enterprises is currently inefficient: even though some relevant data exists,

accessibility problems may either make it difficult to utilize or prevent its use completely. The lack of

common practices and modelling methods causes unnecessary costs and makes it difficult to utilize existing

resources. The target of the work introduced in the paper is a doctoral degree, the contribution being a

comprehensive set of architectural principles and practices to improve industrial information exchange and

business collaboration.

1 INTRODUCTION

The base domain of the work presented in this paper

is industrial information exchange. The term

industrial refers broadly to the various branches of

industry. It includes, for instance, process industry

and piece goods industry as well as the utilization of

mobile machines. Information exchange refers to

passing information from one entity or enterprise to

another. Service architecture is an architectural style

common in the information systems of modern

enterprises, and collaborative business processes

refer to the processes of running business between

partners.

The area of information technology to which this

paper is related has several challenges. The problem

is not always to get more data required to perform

tasks but to access existing information to make it

better utilizable. In addition, even if some

information is available, if there is no reasonable

medium to exchange it then it will be difficult to

store it for later utilization. Maintenance is an

example of an area where such information

management challenges are present. To preserve the

value of a piece of equipment, appropriate

maintenance is required. However, a lot of

information is required for a well-performing

maintenance program. In industrial plants, the reality

may be that the original engineering data is missing

so finding replacement parts may be problematic. In

addition, timing is very significant to get the best out

of maintenance: too early maintenance may cause

extra costs, and too late maintenance may cause

breakdowns and downtime.

The research ideas presented in this paper are the

beginning of doctoral studies, targeting to a doctoral

thesis. The tangible progress from the research point

of view, in addition to this paper, is an article to be

presented in ICEIS 2014. There has also been

research and practical work with industrial

enterprises to improve information exchange. What

is to be done in the future is to explore the principles

required to enable information exchange that is more

advanced and meets business needs better than the

current technologies.

The drivers of this research are enterprises. Real-

world scenarios with genuine business requirements

will be presented in coming publications, and the

work related to those scenarios will form the basis of

the ideas and the contribution of the work.

The rest of this document is organised as

follows. Section 2 explains research context. Section

3 sets objectives and section 4 discusses the

methodology to reach them. Finally, section 5 gives

conclusions and future work.

Kannisto P..

Enhancing Industrial Information Exchange in Service Architectures and Collaborative Business Processes.

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

2 RESEARCH CONTEXT

2.1 Background

This section explains the background and the

motivation of the work. The work is in the very

beginning so the final objectives are still inaccurate

and open for changes and discussion.

In industry, a lot of information exists in

different information systems but its utilization is

problematic. System integrations must be

implemented to access the data, but they are difficult

and laborious.

A better access to the information would

facilitate at least two actions: (1) delivering

information to partners as such, (2) processing

information to gain added value and either utilizing

the generated data locally or distributing it to

partners.

2.2 Data Exchange Challenge

As any information exchange, industrial information

exchange is challenging due to the heterogeneity of

the information models of the various systems. Even

between enterprises performing similar actions (such

as running similar chemical processes or

manufacturing similar piece goods), there may be

considerable differences in how data is stored in the

information systems of the enterprise (Figure 1).

Some type of data collected by one enterprise may

be completely missing from another, or its

sustenance may be neglected, or its data format may

be different. This may be a real challenge for the

industrial partners as they have to adapt their

business to the differences of enterprise data models

even if they were offering similar services to all of

their customers. Any additional work required for

the adaptation causes unnecessary costs that do not

have any value from the production point of view.

The difference of system data models reflects to

system interfaces. Currently, to integrate two

systems of separate enterprises, a considerable

amount of work is required so the value expected

from the integration must be high. If the amount of

data to be exchanged is low or if it is considered too

invaluable, no integration will be performed.

However, if that information is important anyway, it

must be exchanged manually, or worse, it will not be

exchanged at all. If some useful information exists,

it is far from the ideal of collaboration if bad data

accessibility makes it unusable.

Due to integration challenges and the high

price of system integration with current tools and

Figure 1: Exchanging data between heterogeneous systems

or enterprises.

methods, a lot of information is exchanged

manually. Compared to electronic data exchange,

more laborious manual communication is required to

reach the same business value. In addition, if the

information exchange was to be tracked later,

problems may occur as discussions by email or by

phone rarely leave any easily accessible log entries.

Besides, one of the most important business

functions is invoicing as it will generate revenue to

enterprises. If information exchange is manual,

invoicing related to the provided service will require

manual work as well, and it is also subject to human

errors.

To conclude, several points are suggesting the

benefits of system integration but its high price is

problematic. This is due to the heterogeneity of

enterprises.

2.3 Data Management Challenge

As from the data exchange point of view, the

diversity of enterprise data models is a challenge for

data management as well (Figure 2). While some

information may exist, it may be too difficult to

access it. The information could even exist in some

physical media (such as DVD) that is only

accessible by humans. That is, the case may be that

an enterprise practically exploits only a fraction of

some information storage because the access to it is

too expensive. In many cases, existing information

would enable building added value.

In industry, data management is not only about

information systems but also about devices. As the

computational capability of devices keeps

improving, it is advantageous if their data can be

accessed for use. Such information can include, for

example, condition information that suggests when

maintenance is required. Having more accurate

information about devices may enable more efficient

ICEIS2014-DoctoralConsortium

use of workload for maintenance and other actions.

Figure 2: Managing data in heterogeneous systems.

The lack of information access causes unnecessary

costs. Labour is required to check the details that

could be retrieved quickly from data. Data once

produced cannot be utilized anymore. Another

problem is that the sustenance of existing data may

be too difficult. After several years with no

maintenance, the reliability of data can be low – if

one cannot trust the data, does it have any use if a

human being must check data correctness anyway?

That is, it should be easier to not only collect and

store data but also integrate it so its potential can be

exploited for the actual business of the enterprise.

The data management challenge occurs

especially when a business partner needs data from

several systems. The more fragmented the enterprise

architecture is, the more significant is the problem.

Due to the quick evolution of business, new

information systems, constant organisational

changes and constant enterprise fusions, information

fragmentation is expected to be typical rather than

exceptional.

In summary, accessibility problems make data

management needlessly difficult. The result is that

information cannot be utilized as a resource as

effectively as it should.

2.4 Events

In addition to data exchange and collection

challenges, one important point of view is events.

Various types of data are generated by various

systems and devices, and it is meaningful to interpret

that data to detect when some business action is

appropriate. This gap – from data to business actions

– is bridged by events that are detected in constantly

changing data. As the number of data changes may

be simply too large to handle, only some of them are

observed to detect events. Moreover, not all the

detected events are likely to trigger a business

action. This can be illustrated as a triangle (Figure

3). On the bottom, the number of items is large but

their significance is low, while items on the top are

fewer but they may be very significant for the

enterprise. Generating events and triggering business

actions from events has been presented by, for

example, Michelson (2006) and McGovern et al

(2006). Practical event-based architectures have

been developed by, for instance, Dunkel et al. (2011)

and Terfloth et al. (2006).

Figure 3: Data is utilized to detect events that may lead to

various business actions.

While events are an important concept alone, they

are also closely related to the problems presented in

the previous subsections. Data collection and

exchange is present even in the generation of events.

Discovering events to react to them with correct

business actions can be beneficial to one enterprise

or provide competitive advantage, but it can also

bring added value to collaborative industrial

business. Through events, a business partner may

improve their service in a way that might be

impossible or at least harder or slower if correct

business actions were to be triggered by humans.

2.5 Related Work

The issues of enterprise information exchange have

been studied by several authors before. While data

exchange between enterprises is the main concern of

this paper, even system integration inside a single

enterprise is related.

The challenges of inter-enterprise data exchange

have been addressed by Chen & Doumeingts (2003).

They recognize that ICT systems contain the data

forming the essential knowledge, which is the basis

of business. The paper proposes that three technical

domains should be combined to improve the basis of

data exchange: Enterprise Modelling, Architecture

& Platform and Ontologies.

Hausladen & Bechheim (2004) discuss the

aspects of optimizing industrial business processes

with E-maintenance, a maintenance process that

exploits modern IT and communication technology

EnhancingIndustrialInformationExchangeinServiceArchitecturesandCollaborativeBusinessProcesses

for better results. The result is that a comprehensive

business process analysis and documentation are

required. Finally, the utilization of an E-maintenance

platform is suggested.

Han & Yang (2006) propose an E-maintenance

system to improve the performance of maintenance

operations and to gain competitive advantage. They

suggest having a local maintenance system in each

production plant and a single maintenance centre

that provides help when the abilities of local

maintenance are not sufficient. Information is shared

comprehensively by effective communication

methods.

Vernadat (2007) discusses how the information

systems of enterprises can be designed for easier

collaboration. The mutual trust of organisations is an

aspect that has not been addressed enough this far.

Furthermore, collaboration is not only about

technical issues but also strategy, organisation and

people. Customers should form the basis of the

enterprise architecture. Flexibility should be

promoted in design: for example, loose coupling and

asynchronous communication should be favoured.

Chen et al. (2008) have studied the challenges

related to enterprise architectures and problematic

issues that cause shortcomings. It is stated that a

common terminology and a common ontology have

been missing, and there have been several proposals

that cover them but only partially. Additionally,

there have been no proper methods for comparing

architecture proposals, no interoperability has been

possible between existing architectures, standards

have not been mature enough, and no proper

architecture description methods have existed.

Several suggestions to overcome the problems in the

future are given, covering the development process,

tools and design principles.

Muller et al. (2008) review the status of E-

maintenance. Several research and other working

needs are addressed including the adoption of

standards to promote interoperability, adopting of

new technologies to raise the intelligence of devices,

more comprehensive process modelling and the

development of new E-maintenance systems.

Finally, the current knowledge must be analysed in

order to create a new framework to form the

groundwork of E-maintenance.

Panetto & Molina (2008) write that system

integration in the manufacturing domain organizes

machines and people as a system. They state that

current middleware and standards based systems

often fail to scale well so more research is required

to overcome the problems. They propose that the

introduction of semantic web services could help

overcoming the problem.

Chituc et al. (2009) propose a conceptual

framework for collaborative interoperability. It

consists of six elements: messaging service,

collaboration profile, inter-organizational

collaborative activities, a centralized repository, a

set of essential documents and a performance

assessment service. While the coverage of the

framework is wide, there is no implementation

following the principles as far as is known.

Vernadat (2010) discusses the issues of

enterprise interoperation. While the current

technologies and service orientation make

interoperation possible, there are still unaddressed

issues such as data semantics and organizational

support. In addition, there are shortcomings in, for

example, security, language support in multilingual

cases and confidentiality.

Clark & Barn (2011) suggest promoting loose

coupling and complex component interaction in

enterprise systems by favouring Event-Driven

Architecture (EDA) over conventional Service-

Oriented Architecture (SOA). However, as there has

been no modelling notation specifically for EDA, a

proposal is introduced together with a simulation

language. The modelling notation is an extension to

UML (Unified Modelling Language), a common

language in software engineering.

Da Xu (2011) surveys the state of the art of

enterprise information systems. The evolution of

Enterprise Resource Planning (ERP) systems is

discussed as well as Enterprise Application

Integration (EAI). Originally, the term EAI covered

only the integration of systems in one enterprise but

it has later extended to cover integration with

partners as well. Multiple technologies facilitating

inter-enterprise communication are suggested,

including SOA and XML (Extensible Markup

Language). While the paper focuses mostly on the

point of view of a single enterprise, it effectively

explains the current situation of enterprise

information management.

Several enabling technologies have been

suggested but a concrete overall solution is still

lacking as additional layers are still required on the

enabling technologies; that is the gap where this

work is targeted to. In addition, even if the typical

business process elements such as quotation, order

and delivery were covered, the requirement to cover

technical data would still be unaddressed. There may

be a lot of similarities in business processes between

different branches, but the format of technical data

varies inevitably.

ICEIS2014-DoctoralConsortium

2.6 Research Questions

Even though there are several technologies to take

control over data exchange and data management

challenges, the problem that remains is that there is

no methodology to control everything as a whole.

While the existing technologies contribute to some

specific detail, their functionality is insufficient from

the point of view of controlling data in the ever-

changing business environment. That is, there are

several enablers, but the actual solution is missing.

This is illustrated in Figure 4: more architectural

principles are required. Not only should the business

of a single enterprise be considered but also the

collaboration between multiple organisations.

Figure 4: Architectural principles are required to fill the

gap between business requirements and enabling

technologies to bring more control over business

collaboration

From the introduced research problem, the following

questions arise.

1. Information system architecture

a. What kind of architectural solutions promote

data management in various systems?

b. What components are required to build a

concrete collaboration platform?

2. Integration

a. How to make a collaboration platform

customizable enough to meet the diversity of

industrial enterprises and their business?

b. How to meet the diversity of device and

machine related data in industrial systems?

3. Collaboration

a. What kind of architectural solutions promote

collaboration?

To address the questions, a lot of knowledge is

required. The fields include enterprise collaboration,

data management and event-driven architectures. To

understand the business requirements of enterprises,

it is required to receive steering and advises from the

personnel in the business.

3 OBJECTIVES

This section gathers the objectives of the work. As

there are several high-level objectives, the goal is to

focus in the chosen domain as a whole rather than to

contribute to a narrow area. From a domain point of

view, high-level concepts can be considered

strategic in the sense of setting the coarse common

direction of low-level actions. While low-level

functionality is what realizes systems as a whole, it

is important to reach a consistent overall result from

them. Even though industry domain is wide, is does

not mean the work itself should have a wide focus;

instead, the work is related to specific architectural

questions that occur in several areas in the domain.

The high-level objective of this work is to study

ways to improve what currently exists. As the result

of the work, more efficient processes and ways of

working are expected while the core actions and

goals of business processes might remain as they

are. Several paradigms and ideas suit well for

different points of view. The objective is to gain

technical contribution that is not limited to any

specific industry domain but can be applied in

several areas. The final objectives can be given as

follows.

Contributing to Information System

Architecture. In the large scale, architecture is

paramount as it effectively sets the limits of what

kind of functions can be included in the resulting

system or system group. In managing and

maintaining a running system, several questions

arise. What kind of architectural choices are the best

to enable a system that can be customized at

runtime? What if the system is distributed in a

geographically wide area? What if some

customization should be managed globally but local

customization is also required?

Contributing to Information System

Integration. Integration refers to connecting

information systems so that information can be

exchanged between them. While integration as a

concept has existed since long, there is a lot to be

improved in terms of the required human work or

adaptability when business requirements or systems

evolve. As the amount of available information is

constantly growing in industry, more and more

integration requirements arise, which raises the

importance of integration-related improvements.

Could the concepts of integration be improved to

have a better control over system interaction and

system management?

Contributing to Business Collaboration.

Business collaboration refers to interaction between

EnhancingIndustrialInformationExchangeinServiceArchitecturesandCollaborativeBusinessProcesses

two or more business organisations that provides

advantage for all parties. Whatever the collaborative

function is, it can be executed in any of the

organisations or divided to be executed in several of

them. One important point of view of collaboration

is that it can generate added value from existing

systems. According to Marttinen (2013), a

significant challenge is the ownership of data and

processes. While each party takes care of its own

business, collaborative business processes are not

explicitly owned by anyone as they occur between

enterprises. In addition, it is important to recognize

which party has the ownership of each type of data

required for collaboration. In industry, a lot of

information may have its origin in a location other

than where it is utilized so managing information

exchange is crucially important.

Finally, the contribution of the thesis will be a

comprehensive set of principles about designing

system architectures to support industrial

information exchange. The business process point of

view, both internal and collaborative, will be

emphasized. As the field of science is applied and

practical, the contribution will not be entirely new

technologies but rather an experimentation of

applying practices and technologies. The practical

drivers of the work being real-life enterprises, the

contribution will be close to current business needs,

providing added value in near future.

The tangible result will be contributing to both

the efficiency and the effectiveness of information

management in industry. It will improve the

understanding of the correct ways to design

collaborative information exchange. Efficiency

comes from being able to manage information with

less work so personnel can focus on what is valuable

rather than spending time on digging information

whose retrieval should be automatic. Effectiveness

comes from exchanging more information than

previously. This results from the improved

availability of data that may even exist today but in a

format or system not easy to access.

However, it is also evident that the expected

outcome will evolve over the writing period of the

thesis. The topic being wide and abstract, the author

is likely to learn and gain more understanding thus

setting new targets. Moreover, the understanding of

information exchange needs will evolve in the

enterprises driving the research.

In summary, the expected outcome is a set of

architectural principles to build a well-controlled

layer to support data management and exchange.

The principles should be universal in industry rather

than relate to a specific domain as the actual

challenges are similar regardless of the type of data.

4 METHODOLOGY

The research approach to be applied can be seen as a

combination of two methodologies: constructive

research and design science research. According to

Crnkovic, the idea of constructive research is to

build artefacts to meet a problem so new knowledge

is gained. The contribution of the artefacts can be

both theoretical and practical, and the way solutions

are created is design and development rather than

discovery. (Crnkovic 2010) On the other hand,

design science aims at creating, evaluating and

improving IT artefacts so goals can be reached

(Hevner et al. 2004). According to Piirainen &

Gonzalez (2013), design science and constructive

research can coexist and complement each other.

Based on their analysis, it could be said that the two

approaches have a common goal while their points

of view are slightly different.

The selected research approach is expected to

suit well for this work considering the research

problem and the research questions. New solutions,

i.e. artefacts, will be constructed and designed to

find responses for the questions.

The results of the work made for publications

and other practical work will be exploited to gain

more understanding in the domain. While each

problem must be understood solidly before a

solution can be designed, domain understanding will

constantly improve during the work. Finally, the

gained knowledge will be formulated as the outcome

of this entire research.

5 CONCLUSIONS AND FUTURE

WORK

This document introduces an initial plan for a

doctoral degree. The work is in the very beginning

so the plan is currently not very accurate. In

addition, the requirements of the enterprises driving

the research are not completely clear at this point.

Currently, there is a lot to be improved in

industrial data exchange and data management.

Despite several enabling technologies, there is no

consistent solution to utilize the enormous

collaboration potential of existing information

systems. The problem is not the amount of data but

rather the lack of ways to access and exchange it so

it could bring business advantage.

ICEIS2014-DoctoralConsortium

The objective of the doctoral degree is to explore

the architectural principles required to have a better

control over the situation. Clearly, a new abstraction

layer is required to fill the gap between business and

the enabling technologies. The goal is to make

contribution in the terms of architecture, integration

and business collaboration.

The next step is to make a more thorough

literature review to gain more understanding in the

field of science, what research is already done and

what are the most significant problems. Also, it will

help narrowing the scope of the work. Then, a

publication plan should be created to support the

work and to form the basis of the doctoral degree.

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