Localized Ultrasonic Cleaning for Injection Mold Cavities: A Scalable In Situ Process with Surface Quality Monitoring

As global industries seek to reduce energy consumption and lower CO2 emissions, the need for sustainable, efficient maintenance processes in manufacturing has become increasingly important. Traditional mold cleaning methods often require complete tool disassembly, extended downtime, and heavy use of solvents, resulting in high energy costs and environmental impact. This study presents a novel localized ultrasonic cleaning process for injection molding tools that enables targeted, in situ cleaning of mold cavities without removing the tool from the press. A precisely positioned ultrasonic transducer delivers cleaning energy directly to contaminated areas, eliminating the need for complete mold removal. Multiple cleaning agents, including alkaline and organic acid solutions, were evaluated for their effectiveness in combination with ultrasonic excitation. Surface roughness measurements were used to assess cleaning performance over repeated contamination and cleaning cycles. Although initial tests were performed manually in the lab, results indicate that the method can be scaled up and automated effectively. This process offers a promising path toward energy-efficient, low-emission tool maintenance across a wide range of injection molding applications.

Authors

Institutions

Publication Details

Journal
Technologies
Published
2025-08-11
DOI
https://doi.org/10.3390/technologies13080354
Primary Topic
Injection Molding Process and Properties
Type
article
Field-Weighted Citation Impact
0.00

Funders

Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Localized Ultrasonic Cleaning for Injection Mold Cavities: A Scalable In Situ Process with Surface Quality Monitoring

Deviprasad Chalicheemalapalli Jayasankar, Thomas Tröster, Thorsten Marten
Technologies
Injection Molding Process and Properties
article

Localized Ultrasonic Cleaning for Injection Mold Cavities: A Scalable In Situ Process with Surface Quality Monitoring

Deviprasad Chalicheemalapalli Jayasankar, Thomas Tröster, Thorsten Marten
article en

Abstract

As global industries seek to reduce energy consumption and lower CO2 emissions, the need for sustainable, efficient maintenance processes in manufacturing has become increasingly important. Traditional mold cleaning methods often require complete tool disassembly, extended downtime, and heavy use of solvents, resulting in high energy costs and environmental impact. This study presents a novel localized ultrasonic cleaning process for injection molding tools that enables targeted, in situ cleaning of mold cavities without removing the tool from the press. A precisely positioned ultrasonic transducer delivers cleaning energy directly to contaminated areas, eliminating the need for complete mold removal. Multiple cleaning agents, including alkaline and organic acid solutions, were evaluated for their effectiveness in combination with ultrasonic excitation. Surface roughness measurements were used to assess cleaning performance over repeated contamination and cleaning cycles. Although initial tests were performed manually in the lab, results indicate that the method can be scaled up and automated effectively. This process offers a promising path toward energy-efficient, low-emission tool maintenance across a wide range of injection molding applications.

TechnologiesVol. 13(8)
Paderborn University (DE)
Bundesministerium für Wirtschaft und Energie
Affordable and clean energy
Openalex Percentile: Top 80%
Injection Molding Process and Properties
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.