Product Configuration Automation:

Digital Transformation Platform and Case Study

Alexander Smirnov

, Alexey Kashevnik

, Nikolay Shilov

, Nikolay Teslya

Mikhail Petrov

, Mario Sinko

, Jens Arneving

, Michael Humpf

and Thorsten Kolmer

St. Petersburg Federal Research Center of the Russian Academy of Sciences (SPC RAS), St. Petersburg, Russia

Festo SE & Co. KG, Esslingen, Germany

{mario.sinko, jens.arneving, michael.humpf, thorsten.kolmer}@festo.com

Keywords: Product Configuration, Business Process Automation, Configuration Management.

Abstract: The paper discusses more than 10-year experience in product configuration automation based on number of

joint projects between an academic institution and an industrial partner. During the last years, the research

and development in the era of digital transformation has enabled a shift from conventional company business

processes to digital business processes. In the paper we present several business processes that have been

successfully automated what in turn has significantly decreased the product configuration time as well as

errors caused by the human factor. The following business processes are covered: identcode (product code)

related procurement, product segmentation, delivery class specification, supply chain & production

management; online & offline sales, and customer guidance. We present the developed platform to support

these business processes that consists of 10 workflows. We have integrated the developed workflows to the

company production processes and show that business process execution time in average has decreased by 2

times and for some processes by more than 10 times. At the moment, the developed platform is being

successfully used by the company.

1 INTRODUCTION

Digital transformation is a new trend in the

worldwide economy. Companies automate their

business processes implementing various information

technologies with the aim to increase their flexibility,

efficiency and decrease their execution time.

However, changes in business processes are often

associated with difficulties related to the necessity to

adapt existing data models and well-established

processes to the new ones.

One of aspect related to digital transformation is

the production strategy that determines a fundamental

difference between B2B and B4B companies:

business to business creates products and services to

sell to customers, while business for business

companies create products and services based on the

https://orcid.org/0000-0001-8364-073X

https://orcid.org/0000-0001-6503-1447

https://orcid.org/0000-0002-9264-9127

https://orcid.org/0000-0003-0619-8620

https://orcid.org/0000-0001-7403-5036

needs of customers. Once again, we see that being

able to listen to customers, detect their needs, and

empathize with them is the key difference.

Another important concept related to the digital

transformation is the digital customer journey that is

related of the idea of providing a virtual solution

consultant that bundles knowledge of company

products and their interaction into a system and is at

the disposal of customers and partners (Modic 2017).

Hence, digital transformation is strongly

important for global companies. In the paper, we

discuss a digital transformation platform developed

within the scope of a research project with Festo SE

& Co. KG. Festo is a global player and an

independent family-owned company. The company

supplies pneumatic and electrical automation

technologies to 300,000 factory and process

Smirnov, A., Kashevnik, A., Shilov, N., Teslya, N., Petrov, M., Sinko, M., Arneving, J., Humpf, M. and Kolmer, T.

Product Conﬁguration Automation: Digital Transformation Platform and Case Study.

DOI: 10.5220/0011524100003329

In Proceedings of the 3rd International Conference on Innovative Intelligent Industrial Production and Logistics (IN4PL 2022), pages 115-122

ISBN: 978-989-758-612-5; ISSN: 2184-9285

115

automation customers in over 35 industries. The

products and services are available in 176 countries

with about 20,700 employees in over 250 branch

offices in 61 countries worldwide.

Data-driven digital transformation is the most

popular approach (Gölzer and Fritzsche 2017; Pflaum

and Golzer 2018; Wu et al. 2021). This approach is

basically about analyzing existing accumulated data

and building new (or modifying existing) digital

processes around it. However, in the presented case,

the driving force of digital transformation arose from

the process automation department. The results of the

process automation projects were presented in our

previous publications (Smirnov et al. 2016; Smirnov

et al. 2017). Hence a less popular process-driven

digital transformation approach (Lederer et al. 2017;

Juhasova et al. 2019) was chosen. The idea of this

approach is to introduce the digital transformation for

separate processes with their further integration into

one digital eco-system supported by a common

information platform.

In this paper, we share the success story and

present the results of such a digital transformation

process implemented for Festo SE & Co. KG. The

main scientific contribution is a novel approach to

business process automation for product

configuration. The paper is structured as follows. The

next section presents the related work in the area of

digital transformation. Section 3 presents the

platform. The particular processes are presented in

section 4. It is followed by the description of the

developed platform. The main results and evaluation

of their efficiency are given in the conclusion.

2 RELATED WORK

Authors of the paper (He et al. 2021) propose to use

data mining technology for product family design and

product configuration method development. The

method is based on customer requirement and product

engineering information. They construct association

rule-based classifier for sorting out the best product

configuration schemes as popular product variants.

Authors of the paper (Zhao et al. 2022) focused

on the product platform configuration by recognizing

and utilizing shared product modules for product

families. The approach considers the inherent

relationship between product architecture and

processing activities.

Authors of the paper (Shafiee et al. 2021)

proposed a view-based approach required to fully

conceptualize the knowledge to generate product

configuration systems software. They propose to

include four different views to build or edit all the

required knowledge that increases the quality of such

configuration as well as saves time and resources

while improving overall configuration quality.

The paper (Shafiee et al. 2022) considers

reconfigurable manufacturing systems to quickly

reconfigure production capacities and functionalities.

The authors carried out a case study in an engineer-

to-order manufacturing company to analyze the

benefits of a configurable product before and after

integrating the relevant configuration systems with

reconfigurable manufacturing systems.

The paper (Wang et al. 2022) proposes a

hypergraph-based smart product-service system.

Contrary to the conventional configurators that

emphasize the mapping between technical attributes

and product-service bundles, the proposed framework

introduces the usage of the scenario information,

which is usually straightforwardly expressed by

users.

3 DIGITAL TRANSFORMATION

PLATFORM

We propose a digital transformation platform that is

based on company business processes. Digital

transformation allows taking into account rules as

well as making the platform user-oriented.

The platform is based on several workflows.

Every workflow is responsible for carrying out

required action(s) by one or several types of users.

Different types of users can have the same functions

in scope of a workflow or different ones. A workflow

can support a company business process or support

some auxiliary processes required for other

workflows. Besides, the digital transformation

platform supports rules that enable decreasing the

human factor during the data maintenance by

employers.

All data maintained in the digital transformation

platform have SAP synchronization interfaces. Based

on the amount of data and complexity of calculations

it can be either online import/export or a script that

runs nightly and implements everyday data exchange

between the digital transformation platform and the

company’s ERP system based on the SAP. Also, the

data maintained in the digital transformation platform

is used in the “Product configurator” system (see

Figure 1). The developed digital transformation

platform supports processes to maintain (1) product

characteristics as well as product families that define

typical features for a set of products; (2) code scheme

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that determines rules for particular product;

(3) product including segmentation, delivery, and

procurement. Based on these data it is possible to

generate strategies related to production and sales as

well as product management.

Figure 2 shows a typical ordering process on an

example of the EU market. The ordering process

includes several business processes as well as rules

and participating users. A customer from Germany or

Italy (DE/IT) makes a request about a product. The

request comes to the Festo European office (Festo

EU). Based on the information from the identcode

(product code) related procurement (IRP) the

platform identifies if the product can be delivered or

it should be produced and then delivered. If the

product is available in stock, the delivery class is

determined based on the product segmentation (Festo

CSC). If the product needs to be produced, its

delivery class is determined based on the local

delivery class information (EU).

Figure 3 illustrates the overall digital

transformation process implemented in the developed

platform. The rows are the processes automated via

the platform. The columns are the digital

transformation steps. They include (i) gap analysis

(identification of process performance, automation

objectives, and how to meet these), (ii) design of the

digital processes, (iii) development of the

corresponding workflows and supporting software

tools, (iv) deployment of these, (v) integration with

other existing digital workflows, and (vi) refinement

(discovering and removing deviations,

inconveniences, and missing functionality).

We designed every workflow based on the

mentioned bellow digital transformation steps. As a

result, every designed workflow passed all these steps.

4 BUSINESS PROCESSES

The section describes the company business

processes that we automated. It includes identcode

management, segmentation, delivery class

maintenance, identcode related procurement, and

phase out. Bellow we describe in detail each of them.

Figure 1: Digital Transformation Platform.

Figure 2: Ordering process at the example of Europe.

Rules

User

Business

Processes

Employers

Digital Transformation Platform

Characteristics, Product Families

Rules

SAP

Product

Customers

ode

cheme

Products

Strate

ies

Mana

ement

Product Conﬁguration Automation: Digital Transformation Platform and Case Study

117

Figure 3: Digital Transformation Process based on the presented platform.

The identcode and order code team is responsible

for code scheme generation based on the predefined

rules (Smirnov et al. 2013). The identcode code

consists of series from a product classification

ontology (Smirnov et al. 2011) describing the family

of the product, characteristics specifying names of the

functions, values specifying different options, and

sector delimiters logically dividing the identcode into

several sections.

The segmentation panel team (product

management, sales, and supply chain) divide all

products for different segments based on the delivery

time and pricing. Most important functions are

specified as core range products related to one

segment (Complete). Other products are related to the

standard range that is another segment (Standard).

Delivery class alignment teams from different

regions specify the product delivery time and the

possibility to produce it based on customer needs for

different regions. Delivery class is a KPI for a region

related to delivery performance, e.g., 95% of products

should be delivered based on the specified delivery

class.

Global engineering department defines which

values of the identcode should be produced by each

plant. Every customer order is routed to the best

possible plant. For example, an order is entered in

Indonesia. The nearest plant for this order is in

Singapore. If the Singapore plant does not produce

this product, it will be automatically routed to the next

nearest plant (e.g., a plant in China).

The phase out business process allows one to

optimize production facilities for products that are not

ordered frequently. For example, if the product has

been ordered few times for a determined period of

time it is reasonable to phase out the product and the

company does not need production facilities related

to the product.

5 DEVELOPED PLATFORM

In the section we describe in detail the developed

digital transformation platform that supports the

presented in the previous section business processes.

We identified 10 main workflows that we describe in

the section.

As mentioned before the developed digital

transformation platform for product configuration

automation consists of 10 main workflows (see

Figure 4): Delivery Class Alignment (DLCA), Global

View, Code Scheme – NOC, Product Classification

Tree, Core Range, Expert Team for Open Variants

(ETOV): Partnumber Mapping, ETOV: Release

Values, Export, Statistics, CONCode.

DLCA, Core Range, and CONCode are the

workflows for maintenance of the data that are stored

in the platform’s knowledge base as well as exported

Delivery Class Alignment

Global View

Code Scheme

–

NOC

Product Classification Tree

Core Range

ETOV: Part Num

er Mapping

ETOV: Release Values

Export

Statistics

CONCode

Gap

Analysis

Design Development Deployment Integration Refinement

Alignment Team

Head Quarter

Modeler

Product Manager

Head Quarter

Product Manager

Administrator

Digital Customer Journey Team

Research Departmen

Software Development Department

IT Department

All Departments Based on Customer Feedbac

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to the corporate SAP system. These workflows are

responsible to support the mentioned business

processes related to the data maintenance (excluding

the phase out business process)

ETOV: Partnumber Mapping, ETOV Release

Values are auxiliary workflows that allow to setup the

convenient work for other ones.

Global View, Code Scheme – NOC, Product

Classification Tree, are the workflows that present the

stored in the knowledge base information appropriate

to decision support by a user.

Export workflow allows exporting information

from the platform to the company SAP system.

Statistics workflow is aimed at calculating

summary information related to the product and other

product-related information in the platform that allow

one to make strategic decisions (e.g., product phase

out).

The DLCA workflow (see Figure 5) is proposed

to maintain segmentation, delivery classes, and

identcode related procurement. The user should

specify the language, production plant and product

family (series) and the system automatically shows

product structure (product characteristics and values).

The user has a possibility to see the current segment,

delivery class, and identcode related procurement as

well as to set new values.

• Segmentation allows one to split products into

different segments based on local market needs

and defines the delivery performance goal. Two

types of segments are used: Standard and

Complete (KS, KC).

• Delivery class specifies agreed time (in days)

between sales and supply chain for

configuration production and shipment.

• Identcode related procurement includes

definition of production scope of configurable

materials in different plants. In other words, it

specifies which characteristics or values can be

produced in which plant.

Global View (see Figure 6) shows delivery classes,

local focus values, and identcode related procurement

for all plants that allows supply chain stakeholders,

production team, and sales staff to overview this

information and use it for their business processes. The

user can select preferable language and series and see

the product structure for different plants.

The Code Scheme – NOC (see Figure 7) allows

viewing the graphical representation of the code

scheme for the chosen series that includes: identcode

for each product, order of identcode letters and

numbers, and an example of one correct identcode. A

user can use this workflow to see schematic

representation of how the product code is formed.

The product classification tree workflow supports

definition of the identcode business process in the

beginning of the product development process. The

main users of the workflow are product manager,

sales & online sales manager. The product

classification ontology shows the classification of all

company products and supports product type

definition business process, see (Smirnov et al. 2011).

Core Range workflow (see Figure 8) allows

maintaining core ranges for all configurable products

for specified production clusters (a set of plants). The

user can choose the language, cluster, and series.

Maintaining is implemented for each value in defined

production clusters. The workflow enables guiding

the user among core range products as well as guide

him/her to local market needs.

Figure 4: Developed platform that consists of 10 workflows.

Product Conﬁguration Automation: Digital Transformation Platform and Case Study

119

Settings that are set in the tool are transferred

directly to the company product configurator. The

main users of the workflow are segmentation panel

team (product management, sales, supply chain). The

workflow supports the sales business process for

guiding the user to the best option.

ETOV: Part Number Mapping workflow (see

Figure 9) provides a possibility to create part numbers

for product series. The user should choose the

language and series. After that, he/she has a

possibility to create new part numbers for this series.

Open variants mean the configurable products in

SAP. This is an auxiliary workflow that is used for

data maintaining for other workflows.

ETOV: Release Values workflow (see Figure 10)

enables releasing characteristics and values for series

to activate released values per product for sales and

editing examples of the codescheme application. The

user can choose the language and series and decide

which value should be released for production.

Export workflow enables exporting all

information related to the series (Smirnov et al. 2011)

and supports the following formats: xml, json, html.

Statistics workflow enables calculating statistics

regarding to configurable products (the sales report for

one or more materials of the last years). The workflow

allows to calculate how often every value was sold.

The workflow supports the following business process:

sales, phase out. Besides, a special sales campaign can

be launched to push more such products.

ConCode workflow is aimed for identcode

(properties and values) definition based on product

classification ontology (Smirnov et al. 2011) and

creation of digital product (see Figure 11). The

following users use the workflow: product manager,

sales & online sales. The workflow supports the

following business process: identcode definition.

Figure 5: Delivery class alignment workflow.

Figure 6: Global view workflow.

Figure 7: Code Scheme – NOC workflow.

Figure 8: Core range workflow.

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Figure 9: ETOV: part number mapping workflow.

Figure 10: ETOV: release values workflow.

Figure 11: CONCode workflow.

6 CONCLUSION

The paper presents the results of the long-term digital

transformation project in the area of product

configuration implemented for the automation

equipment producer Festo SE & Co. KG. The project

was based on the process-driven approach since the

driving force of digital transformation arose from the

process automation department.

The project resulted in the development of an

information platform supporting such processes as

identcode management, segmentation, delivery class

maintenance, identcode-related procurement, and

phase out. The developed workflows made it possible

to significantly speed up existing processes (Table 1).

Since identified business processes are complex

they cannot be automated based on standard ERP

systems. For this reason, we proposed an approach

that uses the product classification ontology and

automates the business processes.

According to the (S. Ransbotham et al. 2020)

there are five levels of human-AI interaction that lead

to better digital transformation results: (1) AI decides

and implements; (2) AI decides, human implements;

(3) AI recommends, human decides; (4) AI generates

insights, human uses them in a decision process;

(5) human generates, AI evaluates. Our platform is

related to the “Human generates, AI evaluates” level

since the maintaining process is implemented by

humans and the evaluation is implemented by the AI.

Planned future work is aimed at both “in width”

and “in depth” development of the platform. The

former concerns implementation of additional work-

flows and integration of them into the platform. The

latter concerns additional functionality for the existing

workflows based on integration of new technologies

into the platform, such as natural text processing and

machine learning for predictive input, recommend-

dation generation, and validation of the entered data.

ACKNOWLEDGEMENTS

The paper is the result of the collaboration between

SPC RAS and Festo SE & Co. KG. The development

platform was supported by Russian State Research

# FFZF-2022-0005.

Product Conﬁguration Automation: Digital Transformation Platform and Case Study

121

Table 1: Workflow efficiency improvement due to the developed platform.

Workflow Duration without

the platform

Duration with

platform

Improvement

(%)

DLCA workflow, local delivery classes 50 days 10 days 80%

DLCA workflow, IRP 20 days 10 days 50%

Analyzing delivery classes, focus values, and IRP 20 days 5 days 75%

Configurable product maintenance 40 days 20 days 50%

Collection of configuration and procurement

information for all products

10 days 1 day 90%

Development of a product code for a new product 40 days 20 days 50%

REFERENCES

Gölzer P, Fritzsche A (2017) Data-driven operations

management: organisational implications of the

digital transformation in industrial practice. Prod

Plan Control 28:1332–1343. doi: 10.1080/09537

287.2017.1375148

He C, Li Z kai, Wang S, Liu D zhuo (2021) A systematic

data-mining-based methodology for product family

design and product configuration. Adv Eng

Informatics 48:101302 . doi: 10.1016/J.AEI.20

21.101302

Juhasova A, Juhas G, Molnar L, Ondrisova M, Mazari J,

Mladoniczky M (2019) IT Induced Innovations:

Digital Transformation and Process Automation. In:

2019 17th International Conference on Emerging

eLearning Technologies and Applications (ICETA).

IEEE, pp 322–329

Lederer M, Knapp J, Schott P (2017) The digital future has

many names—How business process management

drives the digital transformation. In: 2017 6th

International Conference on Industrial Technology

and Management (ICITM). IEEE, pp 22–26

Modic E (2017) Festo at Hannover Messe 2017 - Aerospace

Manufacturing and Design. In: Online. https://www.

aerospacemanufacturinganddesign.com/article/festo

-hannover-messe-digitalization-integrated-industri

es-33117/. Accessed 6 Jun 2022

Pflaum AA, Golzer P (2018) The IoT and Digital

Transformation: Toward the Data-Driven Enterprise.

IEEE Pervasive Comput 17:87–91. doi: 10.1109/

MPRV.2018.011591066

S. Ransbotham, S. Khodabandeh, D. Kiron, F. Candelon,

M. Chu and BL (2020) Expanding AI’s Impact With

Organizational Learning. In: MIT Sloan Manag.

Rev. Bost. Consult. Gr. https://sloanreview.mit.edu/

projects/expanding-ais-impact-with-organizational-

learning/. Accessed 6 Jun 2022

Shafiee S, Wautelet Y, Friis SC, Lis L, Harlou U, Hvam L

(2021) Evaluating the benefits of a computer-aided

software engineering tool to develop and document

product configuration systems. Comput Ind

128:103432. doi: 10.1016/J.COMPIND.2021.103432

Shafiee S, Zhang L, Mortensen NH, Hansen HN (2022)

Integrating product configuration systems with

manufacturing system reconfiguration. Procedia

CIRP 107:999–1004. doi: 10.1016/J.PROCIR.2022.

05.098

Smirnov A, Kashevnik A, Teslya N, Shilov N, Oroszi A,

Sinko M, Humpf M, Arneving J (2013) Knowledge

Management for Complex Product Development.

IFIP Adv Inf Commun Technol 409:110–119 . doi:

10.1007/978-3-642-41501-2_12

Smirnov A, Shilov N, Kashevnik A, Jung T, Sinko M,

Oroszi A (2011) Ontology-driven product

configuration: Industrial use case. In: KMIS 2011 -

Proceedings of the International Conference on

Knowledge Management and Information Sharing.

pp 38–47

Smirnov A, Shilov N, Oroszi A, Sinko M, Krebs T (2017)

From products to product-service systems: Business

and information system changes

Smirnov A, Shilov N, Oroszi A, Sinko M, Krebs T (2016)

Towards Life Cycle Management for Product and

System Configurations: Required Improvements in

Business Processes and Information Systems. In:

Procedia CIRP

Wang Z, Chen CH, Zheng P, Li X, Song W (2022) A

hypergraph-based approach for context-aware smart

product-service system configuration. Comput Ind

Eng 163:107816 . doi: 10.1016/J.CIE.2021.107816

Wu M, Kozanoglu DC, Min C, Zhang Y (2021) Unraveling

the capabilities that enable digital transformation: A

data-driven methodology and the case of artificial

intelligence. Adv Eng Informatics 50:101368 . doi:

10.1016/j.aei.2021.101368

Zhao S, Zhang Q, Peng Z, Lu X (2022) Product platform

configuration for product families: Module

clustering based on product architecture and

manufacturing process. Adv Eng Informatics

52:101622 . doi: 10.1016/J.AEI.2022.101622

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