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Towards On-Machine Surface Metrology Using Image-Based Frequency Analysis for Surface Variation Analysis
KTH, School of Industrial Engineering and Management (ITM), Production Engineering, Manufacturing and metrology systems. Volvo Group Trucks Operations, Gropegårdsgatan 2, Gothenburg, 405 08, Sweden.ORCID iD: 0000-0002-0013-6333
KTH, School of Industrial Engineering and Management (ITM), Production Engineering.ORCID iD: 0000-0003-3056-781X
Faculty of Mechanical Engineering and Ship Technology, Gdańsk University of Technology, Narutowicza 11/12, 80-233 Gdańsk, Poland.
KTH, School of Industrial Engineering and Management (ITM), Production Engineering, Manufacturing and metrology systems.ORCID iD: 0000-0001-9185-4607
2026 (English)In: Journal of Manufacturing and Materials Processing, E-ISSN 2504-4494, Vol. 10, no 2, article id 69Article in journal (Refereed) Published
Abstract [en]

Machined surfaces contain rich information about machining conditions and system behavior and are typically assessed using off-line, small-area metrology. This study developed and validated an image-based methodology for process-oriented surface texture analysis of end-milled Spheroidal Graphite Iron (SGI), enabling scalable, non-contact monitoring suitable for in-line deployment. End milling trials were conducted under optimized and aggressive cutting conditions and in two orthogonal feed directions (X,Y). Surface topography from White Light Interferometry (WLI) was complemented by Charge-Coupled Device (CCD) microscope imaging. Image processing comprised automatic orientation correction, intensity profile extraction, and frequency-domain analysis via Fast Fourier Transform and power spectral density estimation. Texture metrics (RMS amplitude, skewness, kurtosis, dominant wavelength) were derived from intensity profiles, and two spectral indices were introduced: a Change Index (CI), capturing high-frequency content linked to process disturbances, and a Surface Anisotropy Metric (SAM), quantifying texture directionality. Aggressive cutting increased RMS by 28.5% and shifted skewness by 274% with strong statistical significance. Directional analysis showed 22% higher texture amplitude in Y than X, indicating axis-dependent machine behavior. CI correlated with the machining parameters and stability, while SAM reflected the machine and setup characteristics. Trends were consistent with WLI, supporting the method as a rapid, complementary tool for surface quality and machine condition monitoring.

Place, publisher, year, edition, pages
MDPI AG , 2026. Vol. 10, no 2, article id 69
Keywords [en]
frequency domain analysis, image-based measurement, machining system evaluation, surface texture analysis
National Category
Manufacturing, Surface and Joining Technology Production Engineering, Human Work Science and Ergonomics Signal Processing
Identifiers
URN: urn:nbn:se:kth:diva-378152DOI: 10.3390/jmmp10020069ISI: 001700413600001Scopus ID: 2-s2.0-105031456890OAI: oai:DiVA.org:kth-378152DiVA, id: diva2:2047848
Note

QC 20260323

Available from: 2026-03-23 Created: 2026-03-23 Last updated: 2026-05-06Bibliographically approved
In thesis
1. Machining system evaluation: Towards a standardized methodology for machiningtests and on-machine measurements
Open this publication in new window or tab >>Machining system evaluation: Towards a standardized methodology for machiningtests and on-machine measurements
2026 (English)Doctoral thesis, comprehensive summary (Other academic)
Abstract [en]

The automotive industry is undergoing a major transformation driven by the introduction of new products and powertrain technologies. Although these products are largely expected to be industrialized within existing production systems, there is limited understanding of how such changes affect system performance. Consequently, industry lacks effective tools and methods to manage the transition required to meet future manufacturing demands, particularly in established high‑volume production environments optimized for stable product portfolios.

Against this background, the first part of this thesis analyzes likely scenarios for next‑generation automotive products and their implications for production systems. The analysis identifies two key industrial needs: (1) increased requirements for geometric product quality, and (2) enhanced production system capability to handle a more diverse and rapidly changing product portfolio, i.e., improved system flexibility. These needs must be addressed while maintaining cost efficiency and operational robustness.

To meet these challenges, the thesis proposes two complementary methods for machining system evaluation, using five‑axis milling of ferrous materials as a demonstrator process due to its industrial relevance. The methods are derived from two perspectives. The first is a tactical perspective, enabling standardized and comparable evaluation method of machining system  through machining tests on a purpose‑designed test piece. The second is an operational perspective, aimed at continuous monitoring and verification of the machining system process state to ensure stable production outcomes and increased productivity. This is realized through surface characterization using a CCD microscope, enabling On‑Machine Surface Metrology (OMSM).

The proposed methods are not intended to replace established industrial practices, but to complement them. Together, they support data‑driven decision‑making in both system development and daily production, contributing to a more predictable and robust industrialization of future products and technologies

Abstract [sv]

Fordonsindustrin genomgår en omfattande omställning som drivs av introduktionen av nya produkter och drivlineteknologier. Även om dessa produkter i stor utsträckning förväntas industrialiseras inom befintliga produktionssystem, finns det en begränsad förståelse för hur sådana förändringar påverkar systemens prestanda. Följaktligen saknar industrin effektiva verktyg och metoder för att hantera den omställning som krävs för att möta framtida tillverkningskrav, särskilt i etablerade högvolymsproduktioner som är optimerade för produkter med långa produktlivslängder.

Mot denna bakgrund analyserar den första delen av avhandlingen sannolika scenarier för nästa generations fordonsprodukter och deras påverkan på produktionssystem. Analysen identifierar två centrala industriella behov: (1) ökade krav på geometrisk kvalitet, samt (2) förbättrad förmåga hos produktionssystemet att hantera en mer diversifierad och snabbt föränderlig produktportfölj, det vill säga ökad systemflexibilitet. Dessa behov måste tillgodoses samtidigt som kostnadseffektivitet och operativ robusthet bibehålls.

För att möta dessa utmaningar föreslår avhandlingen två kompletterande metoder för utvärdering av bearbetningssystem, där femaxlig fräsning av gjutjärn används som demonstrationsprocess. Detta på grund av dess industriella relevans. Metoderna har utvecklats ur två olika perspektiv. Det första är ett taktiskt perspektiv, som möjliggör en standardiserad och jämförbar utvärdering av bearbetningssystem genom bearbetningsprov på en särskilt utformad provkropp. Det andra är ett operativt perspektiv, som syftar till kontinuerlig övervakning och verifiering av bearbetningssystemets processtillstånd för att säkerställa stabila produktionsresultat och ökad produktivitet. Detta realiseras genom ytkarkarakterisering med hjälp av ett CCD‑mikroskop, vilket möjliggör On‑Machine Surface Measurement (OMSM).

De föreslagna metoderna är inte avsedda att ersätta etablerade industriella arbetssätt, utan att komplettera dem. Tillsammans stödjer de datadrivet beslutsfattande både vid design av tillverkningssystem och i den dagliga produktionen, och bidrar därigenom till en mer förutsägbar och robust industrialisering av framtida produkter och teknologier.

Place, publisher, year, edition, pages
Stockholm: KTH Royal Institute of Technology, 2026. p. 189
Series
TRITA-ITM-AVL ; 2026:13
National Category
Production Engineering, Human Work Science and Ergonomics
Research subject
Production Engineering
Identifiers
urn:nbn:se:kth:diva-380749 (URN)978-91-8106-619-7 (ISBN)
Public defence
2026-06-03, F3 / https://kth-se.zoom.us/j/62765285597, Lindstedtsvägen 26 & 28, Stockholm, 09:00 (English)
Opponent
Supervisors
Available from: 2026-05-11 Created: 2026-05-06 Last updated: 2026-06-01Bibliographically approved

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Söderberg, VilhelmTomkowski, RobertArchenti, Andreas

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