Development of the supply chain oriented quality assurance system for aerospace manufacturing SMEs and its implementation perspectives

Abstract

Aerospace manufacturing SMEs are continuously facing the challenge on managing their supply chain and complying with the aerospace manufacturing quality standard requirement due to their lack of resources and the nature of business. In this paper, the ERP system based approach is presented to quality control and assurance work in light of seamless integration of in-process production data and information internally and therefore managing suppliers more effectively and efficiently. The Aerospace Manufacturing Quality Assurance Standard (BS/EN9100) is one of the most recognised and essential protocols for developing the industry-operated-and-driven quality assurance systems. The research investigates using the ERP based system as an enabler to implement BS/EN9100 quality management system at manufacturing SMEs and the associated implementation and application perspectives. An application case study on a manufacturing SME is presented by using the SAP based implementation, which helps further evaluate and validate the approach and application system development.

An industrial heterogeneous data based quality management KPI visualization system for product quality control

“…Minitab was used to analyze the quality data of the exterior lighting projectors to ensure the quality of the production process (Simion, 2019). The integration of production data based on the ERP system was completed to achieve quality management (Hussein and Cheng, 2016). A novel ZDM platform, which integrates stateof-the-art information and communications technology (ICT) technologies, artificial intelligence (AI) models and inspection tools, was provided to elevate manufacturing to a superior level of quality (May and Kiritsis, 2019).…”

Experimental Dynamic Analysis of a Breathing Cracked Rotor

“…are connected and exchange information automatically, but also the factory will become conscious and intelligent enough to predict and maintain the machines; and intelligent enough to predict and maintain the machines [5,6]. Many new technologies and methodologies have been developed in the related fields to promote the revolution, such as the crowsdsourcing based new production development in manufacturing SMEs [7], Quality assurance system [8], standardization towards Industry 4.0 [9], wireless device connection [10]. Because of high connection, the health condition of a single machine has greater influence on the factory operation than ever before.…”