Mathematical Problems in Engineering

Decision Making Problems Related to Modular Design Practices or Techniques

Publishing date
01 Sep 2021
Submission deadline
23 Apr 2021

Lead Editor

1Technical University of Kosice, Prešov, Slovakia

2Vellore Institute of Technology (VIT), Vellore, India

3Kalasalingam University, Tamil Nadu, India

4University of Ioannina, Ioannina, Greece

This issue is now closed for submissions.
More articles will be published in the near future.

Decision Making Problems Related to Modular Design Practices or Techniques

This issue is now closed for submissions.
More articles will be published in the near future.


Modularization, or modular design, is a well-known approach subdividing a system into smaller parts called modules. Such parts are designed to be conveniently grouped together so that one module can be independently created, modified, replaced, or exchanged between different systems. Even though the practice of modular design is commonly used in various engineering disciplines, its theoretical/mathematical base is rather fragmented and scattered among different knowledge domains, such as the theory of interdependence and modularity, axiomatic design theory, general modular systems theory, graph theory, complexity science, and system theory. Of these, system theory describes modular systems using mathematical concepts in the most generic way.

Modular products help producers to have many combinations of existing modules, save production cycle times, reduce training cost of employees, rationalize the diagnosis of products or services, etc. Process modularity plays an important role, for example, in terms of mass customization environment, where final products or services are configured by individual customer needs. Therefore, manufacturing and service processes should be designed as independent modules in order to be rearranged easily. The modular architecture of production or service networks brings advantages by allowing completion of final products or services on a just-in-time base.

By reason of the ubiquity of modularity, this Special Issue aims to collect recent original contributions related to developing mathematical/optimization models for decision making problems in product modularity, process modularity, and manufacturing or service systems modularity. We invite authors to contribute original research articles as well as review articles that will cover outlined and related research areas by using mathematical approaches and tools, numerical solutions, computer programs, and data handling procedures. Contributions can be also oriented on a wide range of science-related topics from aerospace engineering, industrial engineering, mechanical engineering, and applied mathematics.

Potential topics include but are not limited to the following:

  • Integrated development of modular product platforms
  • Analyzing system modularity through Design Structure Matrix
  • Engineering system modularity using an axiomatic design approach
  • Mathematical methods in optimizing modular design
  • Modular design in terms of mass customization
  • Measurement methods of product modularity, process modularity, and system modularity
  • Relationships between the different aspects of modularity and complexity
  • Product and process design for Reconfigurable Manufacturing Systems
  • Configuration problems of modular machines, modular process, and modular tooling
  • Resolving product configuration conflicts
  • The concepts, models, and problems of service modularity
  • Supply chain optimization through mathematical models for decision making support
  • Dynamic decision making in mass customization environments
  • Multi-criteria optimization methods in the designing of modular products, services, and systems
  • Customer-centric modular product architecture in context of the Circular Economy
  • Relations between model granularity and modularization of system architectures
Mathematical Problems in Engineering
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Article of the Year Award: Outstanding research contributions of 2020, as selected by our Chief Editors. Read the winning articles.