A MANUFACTURING INFORMATION SYSTEMS
ARCHITECTURE FOR THE 21
ST
CENTURY
Kweku-Muata Osei-Bryson
The Information Systems Research Institute
Virginia Commonwealth University, Richmond, VA 23284
Delvin Grant
DePaul University
School of Accountancy and MIS, Chicago, IL 60604
Keywords: Information Systems Architecture; Manufacturing; Enterprise Integration; Value Chain; Enterprise
Engineering
Abstract: The 21
st
century marketplace poses many challenges for modern manufacturing organizations thus requiring
them to display increased levels of agility supported by an effective information systems infrastructure. The
objective of this paper is to propose an Information Systems Architecture that meets the challenges of
modern manufacturing organizations. For the manufacturing information systems architecture (MISA) to
successfully meet these challenges it must satisfy five objectives: 1. Support the Value Chain Activities; 2.
Support the interactions among the five Interacting Organizational Variables (i.e. Task, Communication,
Technology, People, Structure); 3. Effectively deal with Industry Factors and Forces; 4. Integrate the
organization internally and with its environment; and 5. Address other Enterprise Engineering issues. We
present a MISA that satisfies these five objectives.
1 INTRODUCTION
Modern manufacturing organizations must contend
with social, political, economic and technical
changes (Scott-Morton, 1991) that include
globalization (Rockart and Short, 1991), accelerated
product life cycles, demanding customers, and
rapidly changing technology. These changes require
modern manufacturing companies to display
increased levels of agility supported by an effective
information systems infrastructure (i.e. architecture)
that enables them to exchange information in an
inexpensive, efficient, and maintainable manner
(Nagel and Dove, 1993; Madnick, 1991).
Developing a MISA is difficult and challenging
because it must be balanced with the organization
structure, culture, processes, business strategy,
technology strategy, and the human resources
(Madnick, 1991). Currently there are few
methodologies for the systematic planning and
development of MISA (Grant, 1999). This has fostered
ad-hoc development practices that are associated with
a number of manufacturing problems (Grant, 1999)
In developing this paper, we researched the
literature to identify organizational characteristics
deemed necessary for the success of modern
manufacturing companies. The first characteristic is
that companies must effectively coordinate the
value-added activities of the business (Porter, 1985;
Snow et. al., 1992). Second, companies are viewed
as highly interactive social systems where
technology, tasks, people, communication, and
structure are intertwined (Leavitt, 1965; Grant and
Mergen, 1996; Scott-Morton, 1991). Changing one
part of the social system inevitably affects changes
to other parts and the lack of anticipation of such
changes has crippled companies in the past. Third,
companies operate in a business environment with
external forces (Porter, 1985). Fourth, companies
should be seamlessly integrated both internally and
externally (Grant 2002; Scheer, 2000; Truman
2000). Fifth, effective control-mechanisms for
product/process design and manufacturing are
extremely important for the long-term success of
companies (Grant, 2002; Hammer and Champy,
1993; Davenport, 1995). These and other control-
mechanisms are addressed in the enterprise-
engineering framework of Sarkis et al. (1997, 1995).
457
Osei-Bryson K. and Grant D. (2004).
A MANUFACTURING INFORMATION SYSTEMS ARCHITECTURE FOR THE 21ST CENTURY.
In Proceedings of the Sixth International Conference on Enterprise Information Systems, pages 457-463
DOI: 10.5220/0002618904570463
Copyright
c
 SciTePress

If these control-mechanisms are poorly
implemented, quality control, process control, and
change management initiatives are compromised.
The objective of this paper is to propose a MISA that
meets the challenges of modern manufacturing
companies by addressing the five organizational
characteristics.
2 THE ORGANIZATIONAL
CONTEXT OF
MANUFACTURING
This section describes five theoretical models that
were chosen from the management information
systems (MIS) and engineering literature to support
the five characteristics and objectives listed earlier.
2.1 Value Chain
Every company has a set of value added activities
that are necessary for the production of goods and
services. The Value Chain Model (Cash et al., 1992)
defines this critical set of value-added activities as
Inbound Logistics, Operations, Outbound Logistics,
Sales and Marketing, and Customer Service.
2.2 Five Interacting Internal
Organizational variables
The second characteristic is that companies are a
collection of highly interactive mechanisms of Task,
Technology, People, Communication, and Structure
(Leavitt, 1965; Grant et al., 1996). This set of
organizational variables play an important role in
factory automation (Leavitt, 1965) and in
information systems (IS) (Grant, 1999).
2.3 Five Industry Forces
The third characteristic deals with external forces
from the business environment in which the
company operates. Porter’s Industry and
Competitive Analysis model, well known in
academia and practice, identifies these forces as:
power of buyers, new competitors, new product
substitutes, power of suppliers, and industry rivalry.
2.4 Integration Issues
The importance of integration and its impact on
company performance is well known (Somers and
Nelson, 2003; Madnick, 1991). Grant (Grant, 1995;
Grant et al.; 2002) identified six types of integration,
three of which are relevant to this discussion.
Islands of Technology integration ties together
various islands of manufacturing in order to support
the exchange of information. Socio-organizational
integration is concerned with how well the MISA
supports company goals, objectives, and mission
including internal vertical, internal horizontal,
strategic, and internal temporal integration. Global
integration is concerned with how well companies
effectively operate in the global economy, and
includes how well horizontal and temporal
information are exchanged at the international level.
2.5 Enterprise Engineering
Framework
Modern manufacturing organizations often have to
re-engineer both products and processes in order to
successfully meet the challenges of the marketplace.
It is fairly well known that the re-engineering of a
given process often affects other processes and so
business process reengineering (BPR) should have
an enterprise engineering focus. Therefore, to
address the fifth characteristic, which deals with
engineering mechanisms for process and product
control, we draw on Sarkis et al. (1995). His
enterprise-engineering model consists of four
activities (i.e. Develop Vision and Strategy, Change
Culture, Integrate & Improve Enterprise, Develop
Technology Solutions) that must be addressed in
BPR.
3 THE MANUFACTURING
INFORMATION SYSTEMS
ARCHITECTURE (MISA)
The proposed MISA (figure 1) is made up of eleven
conceptual models, many of which are well known
and have been used in the past with success.
1) Internet Model (IO): This model provides a
blueprint of how the company should be connected
and integrated with its external environment via B2B
and B2C. Relevant issues include supply chain
management, customer relationship management,
employee mobile computing, and business alliances.
2) Intranet Model (IN): This model facilitates the
dissemination of information between individuals,
groups, functions, and departments. It focuses
discussion on the primary information arteries that
exist between islands of technology, business
functions, and groups.
ICEIS 2004 - INFORMATION SYSTEMS ANALYSIS AND SPECIFICATION
458

3) Activity Model (AT): This model represents the
business activities performed by employees of the
company and the information that flow between
them. It is a model of how the business operates and
it serves to document the operations and the
activities of the company. Information from the
activity model aids the development of the data
model, responsibility model, and the knowledge
management model.
4) Responsibility Model (RS): This model
describes the roles that employees perform and the
information requirements to support them. A
connection exists between the activities of
employees and their roles, hence the connection
between the activity model and the responsibility
model.
5) Enterprise Data Model (ED): This model
describes the data objects used or generated by the
business activities, and the relationships between
them. The model is the foundation and the source for
satisfying the daily information and business
intelligence requirements of the business.
6) Database Model (DB): This model describes the
collection of databases that are required to hold the
data that were defined in the enterprise data model.
It should also identify the locations of the databases,
and the rules for maintaining currency and security
of data.
7) Client Server Network Model (CSM): This
model describes the types of computer networks
required to link the various parts of the company or
islands of technology. It makes explicit the systems,
middleware, computing platforms, and operating
systems that need to communicate and how the
communication is handled.
Internet Model
Intranet Model
Responsibility
Model
Activity Model
Data Model
Database
Model
Business
Intelligence
Model
Client
Server
Model
Knowledge
Management
Model
Work Flow
Model
Ontology
Model
Internet Model
Intranet Model
Responsibility
Model
Activity Model
Data Model
Database
Model
Business
Intelligence
Model
Client
Server
Model
Knowledge
Management
Model
Work Flow
Model
Ontology
Model
Figure 1: Manufacturing Information System Architecture
8) Business Intelligence (BI) Model: The Business
Intelligence model addresses non-trivial business
questions that cannot be answered from an
operational database. It includes understanding the
value chains of major customers, primary suppliers,
and major competitors, while improving the firm’s
ability to perform at an optimal level. Part of the
Data Model is represented here.
9) Knowledge Management Model (KM): The
knowledge management model identifies, captures,
stores, manages, and disseminates relevant
organizational knowledge. Knowledge from this
model will find its way in the Activity, Workflow,
and the Ontology models.
10) Ontology Model (ONT): An ontology is a
formal, machine-readable, explicit specification of
the conceptualization that consists of a
representational vocabulary with precise definitions
plus a set of formal axioms that constrain
interpretation and well formed use of these terms
(Bernaras et. al., 1996; Campbell and Shapiro,
1995). It can be used to communicate between
A MANUFACTURING SYSTEMS ARCHITECTURE FOR THE 21ST CENTURY
459

systems, people, and organizations, support the
design and development of knowledge-based and
general software systems, as well as support
knowledge management, knowledge sharing,
knowledge acquisition, and knowledge reuse, and
the specification of vision & strategy.
11) Work Flow Model (WF): The purpose of the
Work Flow Model is to capture, store, and
disseminate information concerning the routing (i.e.,
movement) of widgets and information about them.
It should also capture and disseminate information
about manufacturing machines and robots that are
responsible for manufacturing the parts. The
capability of a robot will affect the path (routing) a
product takes through the manufacturing plant. This
information becomes critical especially in a non-
flexible production environment with demanding
schedules.
4 RELATIONSHIP OF
OBJECTIVES AND
CONSTITUENT MISA MODELS
Given our position that a good MISA must possess
the five characteristics identified in section 1, each
characteristic must be addressed by one or more of
the constituent models of the MISA. Tables 1, 2 and
3 describe the relationships between the MISA
models and the characteristics.
5 THE MODELING PROCESS
The MISA is comprised of eleven interconnected
enterprise-wide conceptual models. Developing such
comprehensive models requires the use of a
methodology that is appropriate for large scale
enterprise-wide IS architecture development. While
there may be several appropriate methodologies, we
choose the 7-phase information engineering (IE)
approach by McDonald (1986). Table 4 shows the
connection between the models, the IE phases and
some of the issues that ought to be considered in the
development of the architecture. In this paper we
only show a subset of the possible combinations,
focusing on those IE phases that differ from
traditional systems development methods.
6 CONCLUSION/DISCUSSION
In this paper, we presented an MISA that satisfies
five critical objectives of modern manufacturing
organizations. We recommended the use of IE as an
appropriate modeling process, and established the
connection between the IE modeling process and the
models of the MISA.
While there is considerable overlap between the
MISA and a generic ISA, there is some significance
difference between them. The overlap stems from
the fact that modern organizations, regardless of the
type of business, require a minimum set of models
as described in the MISA. However, two models of
the MISA (i.e. Workflow, Ontology) stand out in a
manner unique to manufacturing. Although these
two models may be useful in some non-
manufacturing organizations, they are likely to be
critical to the success of modern manufacturing
organizations. The nature of work in manufacturing
places a premium on the movement of parts through
the shop floor. Workflow should be a highly
coordinated and efficient process that pays specific
attention to the route a part takes through the shop
floor, how fast it moves, it design specifications, the
design processes, machine capabilities, and so on.
The ontology model is critical to manufacturing
because many minute and specific details need to be
specified. This level of specification is required by
machines and people and are often in the form of
mechanical drawings and manufacturing processes
that must be translated in a from intelligible to
human and machines. Consequently, there is a need
for formal representational schemas and axioms that
constrain multiple interpretations of data and
process. These two models in conjunction with the
Knowledge Management Model, account for the
bulk of the production issues that are prevalent in
manufacturing. It is these production issues and the
emphasis placed on them that separate
manufacturing from the non-manufacturing
companies
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Table 1: Relationship between MISA models and first three MISA Objectives
Models
Interacting
Organizational
Variables
Value Chain Five Forces
Knowledge
Management Model
Task Inbound Logistics, Outbound
Logistics, Sales & Marketing,
Customer service
Power of Buyers; Power of
Suppliers; New Substitutes;
Industry Rivalry; New
Competitors
Internet Model Communication,
Technology
Inbound Logistics, Outbound
Logistics, Sales & Marketing,
Customer service
Power of Buyers; Power of
Suppliers; New Substitutes,
Industry Rivalry; New
Competitors
Intranet Model Task,
Communication,
Technology
Enterprise Data
Model
Task Sales & Marketing, Customer
service
Power of Buyers, Power of
Suppliers
Database Model Task, Technology Inbound Logistics, Outbound
Logistics, Sales & Marketing,
Customer service
Power of Buyers; Power of
Suppliers
Activity Model Task Inbound Logistics, Outbound
Logistics, Sales & Marketing,
Customer service
Power of Buyers; Power of
Suppliers
Responsibility
Model
People, Task Inbound Logistics, Outbound
Logistics, Sales & Marketing,
Customer service
Client/Server Model Structure,
Technology,
Communication
Inbound Logistics, Outbound
Logistics, Sales & Marketing,
Customer service
Business
Intelligence Model
People, Task Sales & Marketing, Customer
service
Power of Buyers; Power of
Suppliers; New Substitutes,
Industry Rivalry; New
Competitors
Work Flow Model Task, Technology Inbound Logistics, Outbound
Logistics, Sales & Marketing,
Customer service
Ontology Model People, Task,
Communication
Inbound Logistics, Outbound
Logistics, Sales & Marketing,
Customer service
Table 2 Integration Levels and MIS Models
Integration Level MISA Models
Islands of technology Process, Ontology, Intranet, Client Server
Socio-organizational Ontology, Knowledge Management, Responsibility, Intranet
Global Ontology, Knowledge Management, Intranet, Internet, Client
Server
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Table 3: Enterprise Engineering Framework Sub-Activities & MISA Models
Sub-Activity MISA Models
1.1. Develop Vision Intranet, Ontology, Knowledge Management, Business
Intelligence
1.2 Develop Enterprise Engineering
Strategy
Intranet, Ontology, Knowledge Management, Business
Intelligence
1.3 Develop Business Strategy Intranet, Ontology, Knowledge Management, Business
Intelligence y
1.4. Organize for Improvement Intranet, Ontology, Knowledge Management, Business
Intelligence, Responsibility
2.1 Evaluate & assess existing culture Intranet, Responsibility
2.2 Facilitate & commit to improved
communication
Ontology, Intranet, Responsibility
2.3 Share & sell vision Ontology, Intranet, Responsibility
2.4 Build Trust Intranet, Responsibility
2.5 Empower people Responsibility, Internet, Intranet
3.1 Understand the Customer Business Intelligence, Knowledge Management, Data,
Database, Internet
3.2 Understand the Product Knowledge Management, Business Intelligence, Ontology,
Workflow, Data, Database
3.3 Understand & Improve the Process Ontology, Knowledge Management, Activity, Responsibility,
Workflow
3.4 Design & Implement Effective
Controls
Activity, Responsibility, Intranet, Ontology, Knowledge
Management
4.1 Understand the Needs Activity, Responsibility, Workflow, Intranet, Ontology,
Knowledge Management
4.2 Design the System/Solution Activity, Responsibility, Workflow, Intranet, Ontology,
Knowledge Management
4.3 Construct System/Solution Model Activity, Responsibility, Workflow, Intranet, Ontology,
Knowledge Management
4.4 Implement the System/Solution Activity, Responsibility, Workflow, Intranet, Ontology,
Knowledge Management
Table 4: relationship between models, IE phases, and consideration issues
MISA MODEL IE PHASES ISSUES TO CONSIDER
Knowledge
management
Information strategy planning,
Business area analysis
Organization wide best practices; Problems to avoid;
Business unit best practices
Intranet/Internet Business area analysis, Technical
design, Business design
Information content; Which intranets should be connected;
How should they be connected; What information should be
shared
Business intelligence Information strategy planning,
Technical design
Information content; Sources of information; Schema
representation
Enterprise Data Information strategy planning,
Technical design
What has to be represented; What entities are required;
Centralized vs. decentralized DB
Database Information strategy planning,
Technical design
What has to be stored; What questions require answers;
Type of DBMS
Ontology Information strategy planning,
Business area analysis
Organizational terms to be defined; Terms specific to
business units
Client server Business design, Technical
design
Type of data to be supported; Data Traffic patterns; What
type of network; Network Performance requirements
Responsibility Information strategy planning,
Business design
Access to information; Data security; Roles and
responsibilities
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462

MISA MODEL IE PHASES ISSUES TO CONSIDER
Work Flow Information strategy planning,
Business design, Technical
design
Information to support work processes; Process flow;
Efficiency
Activity Information strategy planning,
Business area analysis, Technical
design
What information supports a particular activity; What are
the activities of the business unit; How best to implement
the activity
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