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312. Dust in lacquer, evidence of deviation of process in production lines for spray painting
Tiago Ascenção1, Teresa Pereira1,2, Francisco Silva1
1ISEP - School of Engineering, Polytechnic of Porto, Portugal; 2CIDEM – Centro de Investigação e Desenvolvimento em Engenharia Mecânica, Porto 4200-072, Portugal
This work was carried out in a multinational mobile manufacturing industry. In the painting of parts in MDF (medium density fiber cluster-medium density fibreboard) rejection values lead to a significant loss of productivity. The lines with the highest occurrence of defects are spray painting lines due its complex process. The determination of the causes for the excessive values of rejection of parts is elusive by the multiplicity of factors and parameters involved and the dispersion in the time of their application in the process, not always sufficiently or properly documented. A process analysis methodology was applied for the diagnosis of possible causes of occurrence defects. The impurities defect showed the highest rate, hence the focus of the six months’ data collection from the painting lines. Data analysis was performed using SPSS tool, to find the correlation between parameters, find optimal limits of some parameters and evidence of the influence of same factors. Meanwhile, Kaizen-Lean actions were discussed and implemented conducing to an effective reduction of existing impurities defect rate. The amount of impurities decreased nine times related with initial work values.
348. Towards robust early stage data and knowledge-based inference engine to support zero-defect strategies in manufacturing environments
Manufacturing represents a significant factor of EU’s GDP and its employment. Thus, the efficiency and sustainability of manufacturing processes of high-tech products along with the development of solutions for zero defect applications is more than imperative. This way European manufacturing companies will strengthen their position and keep an advantage in the highly competitive and continuous changing business environment.
Advanced Decision Support Systems (DSS) are considered as a robust technology able to provide an advantage to several manufacturing companies. As part of the Z-Fact0r EU project, an autonomous and self-adjusted early stage inference engine; namely the Early Stage-Decision Support System (ES-DSS) will be deployed. The scope is to facilitate real-time inspection, condition monitoring and control - diagnosis at the shop-floor. The objective is to use the ES-DSS to continuously mine multiple data streams and run the suitable models to monitor operations and quality performance, to classify products on the basis of quality metrics, as well to predict occurrence of defects and deviations from production and quality requirements. Appropriate PAT (Process Analytical Technologies) algorithms will be researched and selectively deployed by the ES-DSS in the use cases of the Z-Factor project to determine potentially critical process parameters. Thus, the ES-DSS inspection and control engine will be able to support zero-defect strategies in manufacturing.
356. An exploratory study on the automated sorting of commingled recyclable domestic waste
Dilan Bonello, Michael Saliba, Kenneth Camilleri
University of Malta, Malta
In material recovery facilities (MRFs) the sorting of waste is typically carried out predominantly manually. In this work, the MRF in Marsaskala, Malta is used as a case study to explore ways in which more automation can be employed to the sorting of commingled recyclable domestic waste. The work addresses first the conceptual design of the process layout and methods. This is followed by the detailed design and development of a universal gripper to replace the human sorter, aimed at removing contaminants from a stream of already sorted material, increasing the purity of the baled material and thereby increasing profits.