27th INTERNATIONAL DEPENDENCY AND STRUCTURE MODELING CONFERENCE - Towards Sustainability Modelling with Attribute Dependency Graphs - A Case Study on Industrial Robots

Oct 26, 2026

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The paper addresses the growing need to understand the ecological impact of industrial processes. While regulatory compliance is required, pinpointing key influencing attributes is difficult because they are interconnected and multidisciplinary. Lifecycle Assessment (LCA) maps product-related processes and highlights impact-heavy phases, yet it often lacks actionable design guidance. Attribute Dependency Graphs (ADGs) are introduced to connect component-level design detail with product-level sustainability metrics, demonstrated using an industrial robot case study.

LanguageEnglish

CategoryResearch & Report

FormatPDF

Pages9

Reading Time23 min

AccessFree to download

1 Introduction

2 State of the Art

2.1 Literature review

2.2 Lifecycle assessment: A detailed view of product sustainability

27th INTERNATIONAL DEPENDENCY AND STRUCTURE MODELING CONFERENCE, DSM 2025 HOBOKEN, NJ, USA, 24 – 26 September, 2025 Towards Sustainability Modelling with Attribute Dependency Graphs-A Case Study on Industrial Robots Philipp Schröder, Akhil Sathuluri, Klemens Hohnbaum, Markus Mörtl, Markus Zimmermann Technical University of Munich, TUM School of Engineering and Design, Laboratory for Product Development and Lightweight Design, Germany Abstract: The need to understand the ecological impact of industrial processes is increasing. While compliance with regulations is essential, identifying key influencing attributes remains challenging due to their interconnected and multidisciplinary nature. Lifecycle Assessment (LCA) aids in mapping product-related processes and identifying phases with significant ecological impact but often does not provide actionable design measures. This highlights the necessity for complementary modelling approaches that support the derivation of design insights. In this work, we utilize socalled Attribute Dependency Graphs (ADGs) as a modelling language connecting detailed component-level design with product-level sustainability metrics. Using an industrial robot as a case study, we demonstrate (1) the use of ADGs to bridge sustainability criteria with quantitative design details, (2) a modular approach for modelling multidisciplinary properties, and (3) a practical example of their application in an industrial context. Keywords: Sustainability, Modelling, Robotics 1 Introduction Systems modelling emerged as a tool for gaining control over complexity (Hu et al., 2020) . Nowadays, complicated systems are made tangible using modelling approaches. This applies to processes on a business level, where the Business Process Model and Notation (BPMN) is a common framework, or to engineering procedures, where Model Based System Engineering (MBSE) is a state-of-the-art modelling framework. Sustainability is widely recognized as a highly complex challenge (Kirschke & Newig, 2017). Modelling sustainability is essential to systematically identify, assess, and mitigate environmental impacts throughout a product's lifecycle, enabling informed decision-making that promotes sustainable development (Hauschild et al., 2004). By creating sustainability models, organizations can better understand the complex interactions between environmental, economic, and social factors, which is crucial for achieving long-term ecological balance and aligning with global sustainability goals (Knudson, 2023) . However, current modelling approaches can become complex and often require specialized expertise to effectively identify the key drivers of sustainability-oriented quantities of interest. This paper introduces Attribute Dependency Graphs (ADG) as an easily accessible method to understand the impact of specific design variables on the quantities of interest. The approach is particularly suitable for the early development stages, when detailed design information is limited. ADGs are a modelling approach for documenting properties and dependencies between them in a particular way: technical consequences of realized technical attributes are distinguished from requirements and design goals to avoid feedback loops. (Rötzer et al., 2022) . We propose that ADGs can support environmental analysis. The following sections demonstrate the possibilities of using ADGs in this context in a concrete case study. While this work focuses on environmental sustainability and, furthermore, on carbon emissions, the methodology can also be applied to other sustainability aspects. 2 State ofthe Art 2.1 Literature review The literature review is guided by a research plan, shown in Table 1. This plan combines the different core topics of this paper. With the use of 'AND' and 'OR' operators, a search string was created and searched in Scopus; additionally, the keywords sustainability and modelling were selected to narrow down literature in

FAQs

Why is modelling sustainability challenging in industrial contexts?

Sustainability modelling is complex because influencing attributes are interconnected and multidisciplinary, making it hard to identify key drivers of quantities of interest.

What limitation of Lifecycle Assessment motivates the proposed approach?

LCA helps map processes and identify impact-heavy phases, but it often does not provide actionable design measures for deriving design insights.

How do Attribute Dependency Graphs (ADGs) support sustainability analysis?

ADGs link detailed component-level design attributes to product-level sustainability metrics, distinguishing technical consequences from requirements and design goals to avoid feedback loops.

Oct 26, 2026

Upload by aboduw