Research
A system planning method based on templates for large-scale
manufacturing information systems
H. Morihisa
*, R. Oshita, H. Furukawa, J. Kanda
Nippon Steel Information and Communication Systems Inc. (ENICOM), 1 Fuji, Hirohata, Himeji Hyogo 671-1188, Japan
Accepted 19 August 1998
Abstract
In the ®eld of manufacturing, there is a need to develop large-scale manufacturing information systems. This is especially true in the Japanese steel manufacturing industry where CIM is the core management technology. But developing such systems requires large amounts of time and manpower, and furthermore, these type of projects are very dif®cult to manage. Therefore, in order to ease the process of analysis and design, we propose procedures based on a two-dimensional template with speci®c criteria for large-scale manufacturing IS architectures. In each manufacturing system, there are two important elements that correspond to the two dimensions of the template. One is a functional category and the other is a management structure. We show here the effectiveness of applying this method to system planning of large-scale IS in one representative steel manufacturing plant.#1999 Elsevier Science B.V. All rights reserved.
Keywords:IS planning; Evaluation of planning system; Planning system model; CIM; Steel plant
1. Introduction
In the ®eld of manufacturing, there is a great need for the development of large-scale systems. For exam-ple, in the Japanese steel industry, computer integrated manufacturing (CIM) has become the core manage-ment technology since the latter half of the 1980s [4]. CIM depends mainly on large-scale manufacturing information systems (IS). Therefore, high-quality ef®-cient system analysis, design and development are required in the ®eld of manufacturing. Furthermore, it is dif®cult to manage large-scale manufacturing IS and such systems demand large resources, particularly of manpower and development time. Therefore, it is
important to have an effective method with which we can analyze, design, develop and manage large-scale manufacturing IS.
In large-scale system development, common con-cepts concerning system methodology and system architecture are very important. A system develop-ment methodology using templates of speci®c manu-facturing system architecture is one example.
However, current methodologies for required and structured analysis have some problems in the process of transformation from the logical to the physical
model because of the lack of precise modeling criteria. To cope with this problem, we have analyzed the entities in the manufacturing process at steel plants and the management structure in the ®eld of manu-facturing. As a result of this investigation, we propose an analysis and design method based on a
two-dimen-*Corresponding author. Tel.: 36-1014; fax: +81-792-37-2011; e-mail [email protected]
sional template that is effective in the implementation of large-scale manufacturing ISs. Also, we illustrate the effectiveness of this model by applying it to the development of an actual information system for one steel manufacturing plant in Japan.
2. Outline of the problem
2.1. Scope
Characteristics of the system for this steel manu-facturing plant are as follows [2, 5]:
1. System type: multistage process production; 2. Constraints: nonstop operation;
3. Evaluation criteria: quality, cost, delivery and cus-tomer satisfaction; and
4. Control elements: working schedule and produc-tion lot size.
Additionally, characteristics of the IS for this steel manufacturing plant are as follows.
1. The IS have the following hierarchical structures: the process control layer, operation on-line layer and production management batch layer.
2. The IS have the function of planning company-wide optimal management strategies in order to assure quantity, delivery and quality of the products to customers, and, above all, to improve service quality so as to strengthen competitiveness in areas other than price.
2.2. Current methodology and their problems
We have been making use of the revised Demarco's integrated requirement and structured analysis meth-odologies which are shown in Fig. 1 [1, 2, 3].
Structured analysis consists of four phases: prepara-tion of the present physical model; preparaprepara-tion of the present logical model; preparation of a future and extended future logical model; and preparation of a future physical model. The structured analysis meth-odology gradually results in detailed design through the expansion possible through the use of data ¯ow diagrams, entity-relation diagrams and state-transition diagrams. The preparation of a future logical model from the present logical model calls for a requirement
de®nition, and this may be performed through require-ment analysis, output of which provides the expanded needs.
However, such a total development methodology has certain problems that must be overcome, espe-cially in logical modeling. These problems are:
1. Analysis of a large-scale system requires a lot of time and effort.
2. It takes a lot of time to transform a logical model into a physical model, because the process of analysis for both the models are separate from one another.
3. There are no precise guiding principles for system architecture and database design.
Therefore, we need modi®ed procedures and guid-ing principles that are useful in system analysis and design. In this paper, we propose a system planning method based on templates as a guideline for the logical system architecture.
3. Template guidelines for large-scale systems
First, we investigate manufacturing systems and show their characteristic functions and management structures.
3.1. Management cycle
In the ®eld of manufacturing, the management cycle is very important and is referred to as PDCA cycle or Demming circle. P, D, C and A denote `plan', `do', `check' and `action', respectively. Fig. 2 shows the
function of the PDCA cycle in the ®eld of the man-ufacturing [2].
In this management cycle, there are three major elements in the ®eld of manufacturing: functions; management cycle; and management elements. We make use of these elements for the improvement of system analysis and design methods [5].
3.2. Function category and management structure
In our method of systems analysis, we use entity-relation diagrams. By analyzing various manufactur-ing IS, we realized that there are some critically important entities: these are the critical success factors (CSF). In the ®eld of manufacturing plant manage-ment, CSF are quality, material, ordering and schedul-ing and each of them is orthogonal to the others. Therefore, we adopt this function category as one axis of the logical system architecture.
We categorize production business activity into the four business layers required in the business management cycle containing a Demming or PDCA cycle: planning; progress control; operation control; and plant control. We adopt these management layers as another axis of the logical system architecture. Features of each management layer are shown in Fig. 3.
3.3. Two-dimensional templates for manufacturing information logical models
During the ®rst stage of system planning, guidelines for the information logical model, which are easily
transformed to the physical model, are important. Thus, we propose two-dimensional templates for the logical models; their axes are the function cate-gories and management layers. Fig. 4 shows the schema of templates for logical manufacturing models.
The manufacturing information system (MIS) is expressed in the following equation:
MISXSubsystems l;m
wherelrepresents planning, progress control, opera-tion control and plant control andmrepresents quality, material, order and scheduling functions.
This logical model is easily transformed to the physical model. Both the logical and physical models have three structural axes and these structures of the logical and physical model axes resemble one another. Fig. 5 shows how the three axes of both logical and physical models correspond.
3.4. Evaluation of planning and modification
It is dif®cult to decide on the best system archi-tecture by using only one procedure. It is necessary to modify the ®rst architecture when evaluating the system architecture. The items to be evaluated in the IS architecture are listed below:
1. Suitability for PDCA system structure;
2. Partitioning of `De®nition of Problems', `Algo-rithm for Solution', `Policy Making';
3. Consistency and degree of loose coupling of the function category; and
4. Validity and degree of loose coupling of the busi-ness layers.
This leads us to modify and re®ne the system planning. Fig. 6 shows the iterative system planning procedures of the improved method for manufacturing IS planning.
Walston and Felix show that the elapsed time in IS development can be estimated by the equation [7]:
D4:1L0:36;
where D is the duration of the project and L the estimated number of source lines (in thousands). This
equation shows that we can decrease the time required in developing a project if we can divide the system into sub-systems, since we can then develop sub-systems parallel to each other.
Furthermore, Putnam developed the following equation for estimation of development effort [6].
KL3= C3kt4d;
whereKis development effort,Lthe number of source lines (in thousands), Ck a state-of-technology
con-stant, and td the development time. This equation
shows that we can also save development effort if we can divide the system into sub-systems.
4. Results of applying this method to a real system
We applied this method based on templates to one of the manufacturing information systems of a steel production plant in Hirohata works in Nippon Steel. This is the total production management system of one steel plant. The estimated number of source lines of
the system was 500 000 steps in PL/I language. The time available for system development was limited to ca. 20 months because of the time required for plant construction.
According to Walston and Felix's equation, system development duration is estimated at 38 months where as by the Putnam's equation, the development effort is estimated at 934 person-months, whereCkis 11 000
(an excellent environment) and the duration is 38 months. But the estimated duration is over the allow-able limit. On the other hand, if we could develop the system within 20 months, the development effort is estimated at 12 171 person-months, over the allowable limit.
Therefore, we divide the total production management system into some sub-systems by using this template model in order to solve a problem which has contradictory constraints. Fig. 7 shows the outline of our two-dimensional template for the steel manufacturing plant. In this ®gure, there are two hierarchical PDCA cycles. One is the management cycle at the level of entire Hirohata Works while the other is the management cycle at the plant level, corresponding to the `Do' section at the Works level. The `Do' section contains some PDCA cycles. Each box denotes the function of the manufacturing plant and eacharrowdenotes data ¯ow. The results of applying this model are shown in Table 1.
By using the estimated number of source lines of sub-systems, the duration and development effort can be estimated by using the Walston and Felix and Putnam's equation, whereCkis 8000 (a good software
development environment). Results are shown in Table 2.
Fig. 4. Two-dimensional templates schema for logical manufactur-ing systems.
Fig. 5. Mapping of the logical model and the physical model.
Fig. 6. Iterative system planning procedure.
Table 1
Estimated number of source lines (in thousands) of the sub-system
Quality Material Order Scheduling
Planning 111 22 0 0
Progress control 36 18 71 32
Operation control 131 10 25 44
According to our model, the duration is estimated to be 23.7 months (maximum estimated duration) and the total development effort to be 824 person-months.
In reality, this total production management system for one of the steel plant was developed in 22 months with 724 person-months and the number of source lines of the system was 585 000.
5. Conclusions
This paper has proposed the use of templates for large-scale manufacturing management system plan-ning. Through the use of these templates, we have accomplished comparatively high productivity results in planning steel manufacturing plant systems.
Fig. 7. Outline of the two-dimensional template for steel manufacturing plans.
Table 2
Estimated duration (in months: upper) and the development effort (in person-months: lower) of the sub-systems
Quality Material Order Scheduling
Planning 22.3 12.5 0 0
222 18
Progress control 13.2 11.6 19.0 14.3
62 13 111 32
Operation control 23.7 9.4 13.1 16.0
289 5 22 53
Acknowledgements
We appreciate the useful suggestions by Prof. Nor-ihisa Komoda in the Department of Information Sys-tems Engineering, Osaka University in writing this paper.
References
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[5] I. Okinaka, Problems in the Production Management System of the Steel Industry ± An Approach to the Problem of Multi-Purpose Decision-Making, in Preprint of {Z-th Interna-tional Conference on Multiple Criteria Decision Making ± Toward Interactive and Intelligent Decision Support Systems, 2 (1986) 551±560.
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Hiroshi Morihisareceived his BE and ME degrees from Tokyo University in 1978 and 1980, respectively. Since 1980, he has been a system engineer at Nippon Steel Corporation and Nip-pon Steel Information and Communica-t i o n S y s Communica-t e m s I n c . ( E N I C O M ) . Currently, he is also a Ph.D student at the Department of Information Systems Engineering, Faculty of Engineering, Osaka University. His research interest is business information systems planning. He is a member of the Institute of Electrical Engineers in Japan and Information Processing Society of Japan.
Ryota Oshitareceived his BE and ME degrees from Kobe University in 1981 and 1983, respectively. Since 1980, he has been engaged in planning and developing systems at Nippon Steel Corporation and Nippon Steel Informa-tion and CommunicaInforma-tion Systems Inc. (ENICOM). His research interest is business information systems planning. He is a member of Information Proces-sing Society of Japan.
Hiroshi Furukawa received his BE from Tokyo Institute of Technology in 1971. Since 1971, he has been engaged in planning and developing systems at Nippon Steel Corporation and Nippon Steel Information and Communication Systems Inc. (ENICOM). He is now General Manager of System Division 1 in Osaka Regional Office. His research interest is business management system. He is a member of The Japan Society for Management Information.
