Classification of foundry clients using business rules approach

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A R C H I V E S

o f

F O U N D R Y E N G I N E E R I N G

Published quarterly as the organ of the Foundry Commission of the Polish Academy of Sciences

ISSN (1897-3310) Volume 11 Issue 4/2011

145 – 148

27/4

A R C H I V E S o f F O U N D R Y E N G I N E E R I N G V o l u m e 1 1 , I s s u e 4 / 2 0 1 1 , 1 4 5 - 1 4 8 145

Classification of foundry clients using

business rules approach

A. Stawowy

a,

*, R. Wrona

b

, M. Ronduda

c

a

AGH University of Science and Technology, Faculty of Management, Gramatyka 10, 30-067 Krakow, Poland

b

AGH University of Science and Technology, Faculty of Foundry Engineering, Reymonta 23, 30-059 Krakow, Poland

c

Odlewnie Polskie SA, Aleja Wyzwolenia 70, 27-200 Starachowice, Poland *Corresponding author. E-mail address: astawowy@zarz.agh.edu.pl

Received 21.06.2011; accepted in revised form 27.07.2011

Abstract

The paper presents the application of business rules approach for the classification of foundry clients taking into account t he economic and technological attributes. Business Rules M anagement (BRM ) systems allow non-technical business people to change the rules, analyze them for errors, and test and simulate them for impact analysis. Although BRM is focused on business processes improvement, it is possible to use this approach in technology management. The model of classification problem, and the knowledge base as a set of decision tables are presented in the paper.

The results indicate that the proposed business rules tool REBIT, developed by AGH team as the project co -funded by the European Union, is feasible as a complete knowledge base and technology management method.

Keywords: Application of information technology to the foundry industry, Business rules

1. Introduction

In the paper we present the Business Rules Engine (BRE) for the classification of foundry clients. This is one of the possible implementations of the BRE tool named REBIT, developed by AGH team as the project co-funded by the European Union. The engine operates in accordance with general BRM idea and simultaneously may include specific technological knowledge [1]. The classification problem consists in classifying a set of elements correctly by assigning each to one of in advance created

classes, according to the elements’ attributes. Statistical and

econometrical as well as soft-computing methods are commonly used to solve the classification problems; a comprehensive review of them can be found in [2].

A common way to support this kind of decision in business practice is to use the expert systems (ES). Despite various range of their applicability, they are characterized by an invariable, a

priori defined structure. There is a main weakness of ES that would not allow an end-user a simple and functional extension of knowledge base as well as introduction of her/his own research results. It leads to a major decrease in flexibility of such system as well as probable premature ageing of knowledge. As a result, such systems can be neither improved by the users on their own nor with slight help from IT specialists, while such flexibility of BRM solutions is the main source of their increasing popularity.

2. Business rules approach

Business Rules M anagement is one of the latest approach to computer support of business activities: BRM concept is implemented in business practice as Business Rules M anagement Systems (BRM S). Business rules approach is defined as a formal

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so that the business behaves and evolves as its leaders intend [3, 4, 5].

A Business Rule M anagement System is a computer system used to define, distribute, execute, monitor and maintain the decision logic. The major objective of BRM S is to allow describing business processes to be implemented independently of the software system [6].

2.1. REBIT as a BRMS example

The Rebit system, developed by a team from AGH University of Science and Technology, is comparable with leading tools available in the market in terms of functionality, simultaneously prevailing them in many cases in terms of implementation costs and fitting up with domestic market environment. It also takes into account specific requirements of manufacturing companies in the area of technology management. The easily -maintainable tool allows for effective decisions support in such issues as: selection of raw materials suppliers for specific orders, selection of

technology or technological parameters for producing customer’s

order, estimating order production costs, setting prices for non-standard orders, working out the most advantageous parameters of conducting technological processes.

The innovativeness of the proposed solution is based on excluding the logical model of decision-making process beyond the concluding system, allowing thus for its fast and flexible modification with small help from IT specialists.

A unique logical language, with variables as basic element, has been developed for the system needs. Simultaneously, the determinability of formulas used in the language has been maintained and the possibilities of verification of knowledge correctness have been guaranteed. The Rebit modules, apart from knowledge editing, provide tools for a check of: internal consistency (logical non-contradiction of knowledge basis), external consistency (compatibility between the model and the achieved conclusions with external world), ability to provide admissible solutions, completeness (no correctly formulated queries shall remain unanswered), correctness (answers to correctly asked queries shall be correct), non-redundancy (no surplus elements shall be present), optimal internal representation (minimal form). The knowledge is recorded in the form of rules:

IF premise THEN conclusion. Both in case of premises and

conclusions, the variables and, moreover, standard functions or

user’s own functions, can be used. The implementation of a broad

set of variables types (numbered lists, arrays, set lists, etc.) was necessary to adapt the knowledge model to specific technology needs.

Technological problems differ from standard issues supported by business rules approach. In many cases, it is necessary to join declarative and procedural knowledge. This process has to be conducted iteratively (in a loop), what is not possible in most of Business Rules M anagement Systems. In the Rebit system, a modified M icrosoft tool (Workflow Designer) has been applied for integrating procedural knowledge with rule sets. The user can intuitively create a task (project) where she/he will join the sequences, loops or decision-trees with objects (activities) executing conclusion process basing on rules. Inside the single project, the user can construct many workflows, using the available rule sets in many ways.

2.2. REBIT modules

The Rebit system provides a set of tools necessary for creating and exploring knowledge bases. The system consists of four autonomic elements:

1. Declarative knowledge editor,

2. Rules workflow editor,

3. Business rules engine,

4. Clients module, integrating other elements.

Fig. 1. Rule text editor possesses the possibility of controlling and prompting

The Rebit system is the only tool of BRM S class which joins the advantages offered by rule systems with expressiveness of algorithmic programming languages. The user/specialist (manager or technologist), with a little help of an IT specialist, can develop a functional application supporting decision-making processes. A particularly important and unique feature of the system is the possibility of suspending the conclusion process for a virtually unlimited period. When completing the decision-making process requires obtaining additional data (what may be time-consuming), such possibility of conclusion suspending becomes indispensable.

System’s rule engine uses an unique algorithm, which optimizes

the volume of external information that is necessary to obtain the answer for the asked query. The user can settle the cost of obtaining some data by himself (e.g. in case of necessary physical tests of the material parameters) and the Rebit engine will conduct the conclusion process in such way that the most expensive queries will be omitted (if possible).

Special emphasis has been put on establishing a user-friendly and universal IT environment where the tool can be applied. The user can create individual applications, join them into corporate IT network or use the System as a service in SOA (service-oriented architecture) solutions.

The possibility of simulating decision-making processes, allowing to verify the correctness of business and technological

decisions without the risk of making experiments on a „living”

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3. Business rules solution

3.1. The problem specification

The problem consists in classifying a client to one of four

created classes:

A – very good,

B – good,

C – average,

D – poor.

The client classification has a great importance in business cooperation as it can be the basis for orders prioritisation or

discount policy, according to the client class.

In the firm under investigation the client’s attributes consist of

three properties:

– economic attributes (sales value per year, profit margin),

– trading attributes (complaints period, payment time-limit),

– production attributes (specified tolerances, special packing,

external treatment, the level of technical cooperation). The classification system is managed in traditional, manual way, without any IT support. Every change in parameters value causes necessity of rebuilding the system almost from scratch.

3.2. The proposed solution

The classification knowledge has been gathered into decision tables which are the main form of knowledge representation in

Rebit system. The exemplar table for Economics property is

shown in Table 1.

The system uses four decision tables: three for mentioned above properties, and the main table which summarized conclusions from bottom-level tables. The tables hierarchy and

the scheme of conclusion process are presented in Figure 2.

Table 1.

Decision table for Economics property

Premises Conclusion

Sales [000 PLN] Profit margin [%] Economics

> 1 000.00 > 30.00 very good

500.01 – 1 000.00 > 30.00 very good

100.01 – 500.00 > 30.00 good

< 100.00 > 30.00 good

> 1 000.00 15.01 – 30.00 very good

500.01 – 1 000.00 15.01 – 30.00 good

100.01 – 500.00 15.01 – 30.00 good

< 100.00 15.01 – 30.00 good

> 1 000.00 5.01 – 15.00 good

500.01 – 1 000.00 5.01 – 15.00 good

100.01 – 500.00 5.01 – 15.00 average

< 100.00 5.01 – 15.00 average

> 1 000.00 < 5.00 good

500.01 – 1 000.00 < 5.00 average

100.01 – 500.00 < 5.00 bad

< 100.00 < 5.00 bad

The tables contents were automatically translated into the proper rules: for example there are 64 rules generated from main

table, each rule contains three premises with And as the only

allowed operator.

The main advantages of BRM approach, compared with traditional manual system, are:

1. similar, objective clients’ view across all firm departments,

2. easy simulation of the system performance,

3. flexible solution which means that it can follow even rapid

changes in the relations with customers,

4. easy to maintain system; it is no problem to delete, add or

update the rules.

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In order to test the performance of our business rules system we considered three cases which are described in Table 2. It can be observed that the proposed set of rules becomes a complete and coherent knowledge repository which allows for drawing unambiguous conclusions.

Table 2.

Test cases for classification problem

Attributes Case 1 Case 2 Case 3

Sales 810 250 98 500 345 600

Profit margin 5.3 34.8 15.2

Complaints period 3 3 18

Payment time-limit 28 65 42

Tolerances 0.5 1.5 1.0

Special packing yes no no

External treatment no full partly

Technical

cooperation very good average bad

4. Conclusions

Business rules can successfully support a wide range of technology and management decisions, starting from sales management and marketing activities, through product design and configuration, up to production planning and scheduling.

The aim of this paper was to present a possible application of

a rule-based approach in clients’ classification. The proposed

engine operates in accordance with general BRM idea but at t he same time includes specific technological knowledge. The system may help the marketing specialists in identifying strong and week

clients’ attributes, and thus in more flexible approach to business

partners.

The problem under investigation appeared to be not very complicated and declarative knowledge proved sufficient to solve it. The solution described in the paper can be implemented in the computer decision support systems for iron cast manufacturers.

References

[1] A. Stawowy, A. Macioł, R. Wrona, Casting process

selection using business rules approach, Archives of M etallurgy and M aterials, vol. 55, No. 3 (2010) 927-934.

[2] S. B. Kotsiantis, Supervised M achine Learning: A Review

of Classification Techniques, Informatica, vol. 31 (2007) 249-268.

[3] R.G. Ross, Principles of the Business Rule Approach,

Addison Wesley (2003).

[4] B. von Halle, L. Goldberg (ed.), The Business Rule

Revolution. Running Business the Right Way, Happy About, Silicon Valley (2006).

[5] The Business Rules M anifesto,

www.business-rulesgroup.org/brmanifesto.htm

[6] C. Huyck, Lectures on Knowledge Based Systems for

Business, M iddlesex University (2008).

[7] M . Ronduda, Tests of Rebit system in foundry Odlewnie