Abstract
Progress control is a key technology for successfully carrying out a project by predicting possible problems, particularly production delays, and establishing measures to avoid them (decision-making). However, shipyard progress management is still dependent on the empirical judgment of the manager, and this has led to delays in delivery, which raises ship production costs. Therefore, this paper proposes a methodology for shipyard ship block assembly plants that enables objective process progress measurement based on real-time work performance data, rather than the empirical judgment of a site manager. In particular, an IoT-based physical progress measurement method that can automatically measure work performance without human intervention is presented for the mounting and welding activities of ship block assembly work. Both an augmented reality (AR) marker-based image analysis system and a welding machine time-series data-based machine learning model are presented for measuring the performances of the mounting and welding activities. In addition, the physical progress measurement method proposed in this study was applied to the ship block assembly plant of shipyard H to verify its validity.
Highlights
To improve productivity and enhance cost competitiveness, the shipbuilding industry aims to establish smart shipyards that can manage performance through the real-time collection of production information
A methodology that enables objective process progress measurement based on data, rather than the empirical judgment of a site manager, was proposed for shipyard ship block assembly plants
A method was defined for the measurement of work progress by activity that allows for the measurement of overall ship block progress performance
Summary
To improve productivity and enhance cost competitiveness, the shipbuilding industry aims to establish smart shipyards that can manage performance through the real-time collection of production information. The IoT is a digital technology for vertical integration and can provide a solution to automatically collecting and transmitting data throughout the manufacturing process, reducing the time and costs required to secure production data and measure performance. Recent studies have been conducted to improve both the convenience and performance of data collection and streamline production management by converging ICT (information and communication technologies) into existing shipyard production processes. There is still a lack of research into how real-time performance information can be collected at shipyards without the intervention of workers or objective progress measurement based on production data. In this study, an IoT-based performance measurement method is presented that can automatically collect performance data without worker intervention through analyzing the work procedures and facilities used in the ship block assembly process. The proposed method was applied to the ship block assembly plant in shipyard H to verify its validity
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