=Paper=
{{Paper
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|title=How to analyze and quantify similarities between configured engineer to order products by comparing the highlighted features utilizing the configuration system abilities
|pdfUrl=https://ceur-ws.org/Vol-1453/21_ShafieeHvamKristjansdottir_HowToAnalyzeAndQuantifySimilarities_Confws-15_p139.pdf
|volume=Vol-1453
|dblpUrl=https://dblp.org/rec/conf/confws/ShafieeHK15
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==How to analyze and quantify similarities between configured engineer to order products by comparing the highlighted features utilizing the configuration system abilities==
https://ceur-ws.org/Vol-1453/21_ShafieeHvamKristjansdottir_HowToAnalyzeAndQuantifySimilarities_Confws-15_p139.pdf
How to Analyze and Quantify Similarities between
Configured Engineer-To-Order Products by Comparing
the Highlighted Features Utilizing the Configuration
System Abilities
Sara Shafiee1, Lars Hvam2, Katrin Kristjansdottir3
Abstract. 1 Engineering-To-Order (ETO) companies making reach all the advantages that can be gained from utilizing product
complex and highly engineered products, face the challenge of configuration systems, changes in the organization and the
delivering highly customized and engineered products with high supporting systems in the order acquisition and fulfillment process
quality and short delivery time. In order to respond to those are needed [4]. These issues can be solved by double checking all
challenges ETO companies strive to increase commonality between
the outputs generated by the configurator through an automated IT
different projects and to reuse product related information. For that
purpose companies need to be able to retrieve previously designed solution. “All designs are redesigns” has long been a popular cliché
products and identify which parts of the design can be reused and in design research [5]. More generally it has been observed that in
which parts to redesign. This allows companies to reduce many firms the reuse and generalization of past experiences (often
complexity in the product range, to decrease the engineering hours called "lessons learned") is becoming a key factor for the
and to improve the accuracy of the product specifications. In this improvement, in time and in quality, of operational processes [6]. It
article we suggest a framework where product features from the is rational to say that all the attributes of the products and all their
company’s configuration system are listed up in order to compare relations are available in the configuration system; and for every
with previously made products by retrieving information from received order from the customer, changes and specifications for
internal ERP/PLM systems. The list of features consists of defining the product are entered into the configuration system. The idea is to
features with potential sets of values e.g. capacity, dimensions,
make a connection between ERP and the configuration system,
quality of material, energy consumptions, etc. When identifying a
specific previously designed product, it allows access to all of the when generating quotations in the product configuration systems
specifications of the existing product along with the engineering and compare it with the previous done projects saved in the ERP
hours used, materials used, and hours used in the workshop. The system from different perspectives. ETO companies producing
aim of this paper is to make a framework for setting up a database complex highly engineered products have a significant problem
before starting the comparison. when calculating the prices for the presale and sale processes. That
is especially the case when domain experts cannot determine
accurate price curves or when vendors are not providing sufficient
1 INTRODUCTION AND PROBLEM information to be modeled inside the configurator. Therefore
STATEMENT estimates are used or markup factors are added. When
A configurator supports the user in specifying different features of underestimating costs in projects the company will lose profit and
a product by defining how predefined entities (physical or non- when overestimating the cost the customer might go elsewhere
physical) and their properties (fixed or variable) can be combined where he can buy the product at a reasonable price. The accuracy
[1]. Improving the quotation process with the help of configuration of calculations is affected, as previous projects are not easily
systems is a great opportunity for enhancing the presale and accessible and it requires significant work to compare potential
production process efficiency in the companies [2]. There are new projects with previous projects manually in order to find the
several benefits that can be gained from utilizing product relevant information.
configuration systems, such as a shorter lead-time for generating Hvam et al. [1] explains this problem by using an example from
quotation and fewer errors, increased ability to meet customer F.L. Smidth, which is an ETO company selling cement plants. In
requirements with regards to functionality and quality of the this example, the company strives to reuse information from
products, increased customer satisfaction, etc. [3]. Theoretical previously made projects to calculate the most accurate price based
elaboration of the empirical evidence suggests that, in order to on weight and capacity. According to Hvam et al. [1], the price and
weight curves are made by inserting the capacity, price and weight
1
based on information from 3-5 previously produced machines. A
Industrial PhD Student, Management Engineering department, Technical curve is then drawn through the points as is demonstrated in
University of Denmark, 2800 Kgs.Lyngby, Denmark, sashaf@dtu.dk
2
Professor, Centre for Product Modelling (CPM), Department of Figure 4. This allows identification of prices and weights for
Management Engineering, Technical University of Denmark, 2800 machines that have not previously been produced.
Kgs.Lyngby, Denmark,lahv@dtu.dk
3
PhD Student, Management Engineering department, Technical University
of Denmark, 2800 Kgs.Lyngby, Denmark, katkr@dtu.dk
139 Juha Tiihonen, Andreas Falkner and Tomas Axling, Editors
Proceedings of the 17th International Configuration Workshop
September 10-11, 2015, Vienna, Austria
Modular architecture is a term that usually refers to the
construction of a building from different instances of standardized
components, and in manufacturing it is used for interchangeable
units that are used to create the product variants [10]. Dahmus et al.
[11] defines a Modularity Matrix to find the similarities between
product platforms across columns for a single function in the
Figure 1. Price and weight curve for main machines in F.L Smith matrix. Thereafter, architecting of the product portfolio is
recommended to take advantage of possible commonalities through
However, with regards to highly complex products, the price the reuse of modules across different product families. If an
curves are not thought to be the most accurate method as there are existing product has standardized and decoupled interfaces, the
several dependent features and great numbers of neighbors on the design of the next product can re-use heavily from the components
curve. Another important drawback from the price curves is that of the previous product. Holmqvist [12] identifies existing
the user is only provided access to some of the previously made modularization methods and analyses them with regards to their
projects. Therefore the most similar previous projects might be ability to deal with different degrees of product complexity. Based
missed. on that he proves that modularization methods are really useful for
The first benefits of using an automated IT process, where an a simple product architecture but for higher degrees of product
integration between the configuration system and the company’s complexity, when several functions are allocated to several
internal ERP in order to get access to previously saved project physical modules, or large variation of variants, these methods
information, is to avoid time consuming redesigning activities in seem inefficient [12]. Zamirowski et al. [13] presents three
the production phase. This means that it will be possible to produce additional heuristics to find common modules across products in a
the same component or product while spending the least possible product family. By knowing the previously ordered products, there
time and resources. will be the opportunity of decoupling of design and production
Salvador and Forza [7] offer much anecdotal evidence of the tasks.
issues related to product configuration systems. These are listed in The potential benefits that can be gained from using the
terms of: excessive errors, too long time between sales and comparison capabilities between configuration systems and other
installation due to inadequate product information supply to the databases at the companies are summarized in Table 1.
sales office, an excess of repetitive activities within the technical
Table 1. Benefits from reusing the previous projects
office, and a high rate of configuration errors in production. Even if
Area Benefits
there are often concerns regarding product configuration projects
Management 1. Lean management by avoiding all the
and the possible errors in the early phases of deploying the presales, production and sales activity
systems, the confirmation of the configuration system is not the that have been performed before.
only benefit from the mentioned solution. Configuration system 2. Reducing errors and increasing
Salvador and Forza [7] describe product configuration systems development reliability of the configuration system.
as aid systems for the end users or customers for creating 3. Facilitating the testing process for the
configuration systems development.
communication value. Comparing the new project with previous
Standardization, Product 4. Recommending previously successful
ones could also turn into a recommendation system in the projects to the end users.
companies. Felfernig [8] discusses different recommendation planning, Configuration
5. Basis for product standardization.
systems that are divided into Collaborative Filtering (CF), Content system
Product planning, 6. Statistical approach to the information
Based Filtering (CBF) and Knowledge Based Recommendations and market requirements of the
(KBR). The available recommendation technologies in e- management
product.
commerce are potentially useful in helping customers to choose the Product planning, 7. Improve the quality of the
optimal products configuration [9]. It seems that the mentioned Configuration system configuration system, lead time,
idea is similar to the values that come from recommendation manufacturing, sales engineering.
systems. This means that if a 95% similarity between the current
project and a previous project is found, the previous project can be Inakoshi et al. [14] propose a framework for product configuration
re-used and thereby cost related to making the product that integrates a constraint satisfaction problem with a Case-based
specification significantly reduced. This includes costs in the sales Reasoning tool (CBR), where the framework is applied to an on-
phase, engineering and production. Furthermore, this is likely to line sales system. This framework contains the following steps:
improve the quality and the accuracy of the cost estimations. It also
makes it easy to reach an agreement with the customer, and to 1. Case retrieval: similar cases are retrieved from the case
recommend to them a consultancy to confirm the success of the base in accordance with the similarities between the
project by small changes in the order. current query and the cases.
Furthermore, this approach enables companies to analyze the 2. Requirement formalization: a well-defined requirement
products statistically for future product development. Using the consists of the current query and the object function, and
configuration systems and comparing different orders can provide it is supplied to a Constraint Satisfaction Problem (CSP)
valuable information to managers, as it helps them to keep track of solver.
product features and to get an overview of market demands. This
helps companies to be more in control over the product assortment 3. Requirement modification: The well-defined
and eliminates the complexity related to the diversity of product requirement is modified only if there is no configuration
features offered in the production line. and the CSP solver returns no solution back to the CBR
Wrapper.
Juha Tiihonen, Andreas Falkner and Tomas Axling, Editors 140
Proceedings of the 17th International Configuration Workshop
September 10-11, 2015, Vienna, Austria
4. Parts database: a parts database that contains the configuration system to compare with all the previously generated
definition of a product family. It defines the types of quotations, which are documented in a desired database. In Figure
parts, the constraints on parts connectivity, and other 3 the process needed for the comparison accomplishment is
kinds of restrictions on the products. illustrated.
5. CSP solver: The CSP solver receives a well-defined user
requirement and solves the problem.
The physical structure of the configuration system is illustrated in
Figure 2.
Figure 3. The process of comparing and find similar products
3.1 Set up of the database with previous
projects, comparing the configured
products with the previously designed
Figure 2. Physical architecture of configuration system [14] products
This research work has been used as an inspiration for creating a Inakoshi et al. [14] introduce a framework for comparing a product
database development framework and then doing a comparison and configuration that integrates a constraint satisfaction problem with
integrating it with the product configuration system. There is no a Case-Based Reasoning tool (CBR) for a specific case and with
discussion in detail on how to make a database from the ERP specific tool. In this paper the aim is to make a framework in order
system, where all the previous projects are stored. to create a database for the comparison, which allows the
comparison to be done in a standardized way where the currently
available tools and methods can be utilized. Based on literature a
2 RESEARCH METHOD seven step framework has been developed, the individual steps are
illustrated in Figure 4. The process is not a complete waterfall
In accordance with the overall objective, the first phase is focused process, as it is necessary to iterate some of the steps depending on
on the development of the framework, devoted to selecting a the product.
framework for product configuration, which integrates a constraint
satisfaction problem with Case-Based Reasoning tool (CBR) from
previous literature.
The framework development is an ongoing research project to be
developed further and tested by a group of researchers and
practitioners with an applied research background in modelling
products, product architecture, knowledge engineering and product
configuration, software development, combining traditional
domains of mechanical engineering with product configuration and
software development. The framework will be tested in an ETO
company specializing in production of catalysts.
Figure 4. Database set up process in 7 phases
3 SUGGESTED METHOD FOR
IDENTIFICATIO AND COMPARISON 3.1.1 Identify relevant features according to features
BETWEEN PRODUCT FEATURES from configuration model
Previous researchers define different tools and methods to measure Previous research that describes how to use modules across
the similarities between product features. Using configuration different products [13] [15] will be used in order to compare
systems and techniques for comparing products, it is possible to different products. Commonality is best obtained by minimizing
compare different product features that have been ordered with the the non-value added variations across the products within the same
new coming orders. One of the prerequirements for using the product family without limiting the choices for the customers [16].
automatic comparison is to have product configuration system in According to Ulrich [10], if an existing product has standardized
the sales process. The scenario is to use product features in the and decoupled interfaces, the design of the next product can
141 Juha Tiihonen, Andreas Falkner and Tomas Axling, Editors
Proceedings of the 17th International Configuration Workshop
September 10-11, 2015, Vienna, Austria
borrow heavily from the components of the previous product. This technique could be used for finding the projects or products
Thevenot and Simpson [16] discuss a framework where with the same specification but for a high level of similarities. This
commonality indices are used for redesigning the product families could help us to identify some of the product features and then
to align with cost reductions in the product development process search for their range of values.
aligned with the standardized and modularized product structure
incorporated to the configuration system, makes it easier to pick
the relevant features or add them to the configurator. 3.1.4 Classifying the products based on features
E. Lopez-Herrejon et al. [17] introduce Software Product Line For identifying and classifying relevant features in order to make a
Engineering (SPLE) to represent the combinations of features that database, classification techniques are required. Burbidge describes
distinguish the system variants using feature models. how to classify the needs for the product components and coding
them by introducing the Group Technology (GT) method [24].
Martinez et al. [25] then use the GT technique as a base for
3.1.2 Retrieve specifications on previous designed
developing a new GT method [25] they provide an example where
products from ERP / PLM system
the GT technique is used in manufacturing plant where it help in
The current generation of database systems is designed mainly to the processes of minimizing unnecessary variety by making
support business applications and most of them offer discovery designers aware of existing components [24]. The aim of
features using tree inducers, neural nets, and rule discovery classification and coding is to provide an efficient method of
algorithms [18]. One of the fundamental problems of information information retrieval for decision making. To be efficient enough a
extraction from ERP systems is that the formats of available data code must be designed for the particular purpose for which it will
sources are often incompatible, requiring extensive conversion be used [24]. Leukel et al. [26] discuss the design and components
efforts [19]. Knowledge discovery in databases represent the of product classification systems in B2B e-commerce and
process for transformation of available data into strategic suggested a data model based on XML. Fairchild [27] discuss the
information, which is characterized by issues related to the nature application of classification systems and the requirements on them.
of data and desired features [20] [21]. Brachman et al. [22] define Simpson [28] uses GT for adding, removing, or substituting one or
Knowledge Discovery (KD) process elements to be in three steps: more modules to the product platform for product platform design
and customization. Sousa et al. [29] suggest an automated
1. Task discovery, data discovery, data cleansing, data
classification system for specialization of life cycle assessment.
segmentation
First of all they manage to have a conceptual framework for
2. Model selection, parameter selection, model
environmental performance of product concepts. Then, the
specification, model fitting
hierarchical clustering has been used in several applications to
3. Model evaluation, model refinement, output evaluation
show useful ways of grouping objects according to their
KD has a variety of meanings. It includes, at one end the derivation similarities and product descriptors data. Finally, it is used to
of useful information from a database like “which products are develop an automated classification system based on decision trees
needed for the specific amount of engineering hours for algorithms. Sousa et al. [29] also use Matlab and C4.5 decision tree
installation?” [23]. algorithm, which seems to be applicable in all classification cases.
C4.5 is an algorithm used to generate a classification in form of a
decision tree that is either a leaf indicating a class or a decision
3.1.3 Retrieve features from product files and node that specifies some test to be carried out on a single attribute
determining the values value. This algorithm has a few base cases as below [30]:
Most companies use the old technique called “British
classification” when naming different components according to the 1. All the samples in the list belong to the same class. When
product variants. However as the products get more complicated this happens, it simply creates a leaf node for the decision
this technique becomes impractical. In this technique, as shown in tree saying to choose that class.
Figure 5, there is a “surname” of five digits it is the general class of 2. None of the features provide any information gain. In this
an item and the “Christian name” of three digits for an exact case, C4.5 creates a decision node higher up the tree
identity of for the particular item [24]. using the expected value of the class.
3. Instance of previously unseen class encountered. Again,
C4.5 creates a decision node higher up the tree using the
expected value.
Ho [21] introduces OSHAM system generated in hierarchical
graphical browser which is competing with C4.5.
Magali and Geneste [6] propose object oriented modeling
language, Unified Modeling Language (UML) as a standard
modelling of domain knowledge for their research work to
represent field data. The exploitation of the object modeling as an
indexing base is suggested to allow a fast selection of potentially
Figure 5. Expansion of a major class [24] interesting objects during the similar case search [6].
Juha Tiihonen, Andreas Falkner and Tomas Axling, Editors 142
Proceedings of the 17th International Configuration Workshop
September 10-11, 2015, Vienna, Austria
Guillaume et al. [31] developed six heuristics for clustering and The case study is planned based on a group of researchers from the
weighting the logical, syntactical and semantical relationships Technical University of Denmark in collaboration with Haldor
between feature names. The other representation introduced as the Topsoe. The aim is to test and make further developments to the
so-called Product Comparison Matrices (PCMs), can help to make proposed framework. The case study should aim to find the major
a choice, where the aim is to visualize all the products and minor drawbacks in the current framework and refines it based
characteristics through a metrical representation, [32]. on experiment. The main things that will be tested in the case study
are listed below:
3.1.5 Set up database with previous products design 1. Can we retrieve the products’ features out of the ERP
Ramakrishnan et al. [33] give an overview of database design in system?
the following three steps: 2. Can we classify the products?
3. Can we make a data base according to the product
1. Requirement analysis: Understanding of what data is to features?
be stored in the database, what applications must be built 4. How to do the comparison between the new product and
on top of it, what operations are most frequent and subject the previous designed products?
to performance requirements. 5. How to integrate the data base and configuration
2. Conceptual database design: The information gathered in systems? How to make the user interface in the
the requirements analysis step is used to develop a high- configuration system?
level description of the data along with the constraints to
be stored in the database.
3. Logical database design: Database Management System 5. CONCLUSION
(DBMS) has to be chosen to implement the database
design, and convert the conceptual database design into a
database schema in the data model of the chosen DBMS. In this paper we suggest an approach for comparing a new order
that is being configured with previous made configurations, which
are usually stored in various internal systems at the companies.
3.1.6 Comparing the new order products with the This will lead to some advantages such as increased commonality
previous designed products in the ERP/ PLM across different products and reuse of modules across the family of
system products. To achieve the goal of comparing different products a
database for the necessary features is needed. The proposed
There are extensive research works in the field of IT illustrating approach includes 7 separate phases. Finally after the database
different methods to do the comparison in an automated way. setup, the comparison method based on literature will be
Classical Case-based Reasoning tool (CBR) methodologies [34] accomplished and the integration between the configuration system
[35] are based on four tasks, which are: Retrieve, Reuse, Revise and database will be performed. The paper is just mentioning a
and Retain are highly used for this purpose. problem realized as one of the configuration system drawbacks and
Navinchandra’s [36] developed CYCLOPS, which was the first suggests a framework for using comparison method to solve this
system to explore CBR in interactive design. Vareilles et al. [37] problem. To have a generic framework to retrieve data from ERP/
proposed an approach to use ‘contextual knowledge corresponding PLM systems and compare them in configuration projects further
to past cases’ and ‘general knowledge corresponding to relations, research work is required as listed below:
rules or constraints that link design variables’. In this research, 1. Framework testing for a case study and test the available
Constraint Satisfaction Problem (CSP) is used regarding general tools for retrieving and comparing the features.
knowledge and CBR operates with conceptual knowledge. 2. Development of the possible ways to integrate database
with product configuration system.
Magali and Geneste [6] propose a method to define the
neighborhood of the retrieved case to propagate domain
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145 Juha Tiihonen, Andreas Falkner and Tomas Axling, Editors
Proceedings of the 17th International Configuration Workshop
September 10-11, 2015, Vienna, Austria