Abstract
Data mining (DM) with Big Data has been widely used in the lifecycle of electronic products that range from the design and production stages to the service stage. A comprehensive analysis of DM with Big Data and a review of its application in the stages of its lifecycle will not only benefit researchers to develop strong research themes and identify gaps in the field but also help practitioners for DM application system development. In this paper, a brief clarification of DM-related topics is presented first. A flowchart of DM and the main content of the flowchart steps are given in which commonly used data preparation and preprocessing approaches, DM functions and techniques, and performances indicators are summarized. Then, a comprehensive review covering 105 articles from 2007 to 2017 on DM or Big Data applications in the electronics industry is provided according to the flowchart from various points of view such as data handling, applications of DM, or Big Data at different lifecycle stages, and the software used in the applications. On this basis, a diagram of data content for different knowledge areas and a framework for DM and Big Data applications in the electronics industry are established. Finally, conclusions and future research directions are given.
Highlights
Since the internet of things and advanced information technologies (for example, radio frequency identification (RFID) tags and smart sensors) are widely used in manufacturing enterprises for their daily production and management, the product lifecycle management (PLM) processes produce a huge amount of data [1]
This paper presents a comprehensive review of data mining (DM) with Big Data towards its applications in the electronics industry
We can see that the DM with Big Data has been applied to different scenes including product design improvement, manufacturing process optimization, production management and optimization (PMO), production process monitoring and control, quality improvement, customer relationship management (CRM), and so forth
Summary
Since the internet of things and advanced information technologies (for example, radio frequency identification (RFID) tags and smart sensors) are widely used in manufacturing enterprises for their daily production and management, the product lifecycle management (PLM) processes produce a huge amount of data [1]. A Taiwan Semiconductor Manufacturing Company adopts Big Data based advanced equipment control/advanced process control (AEC/APC) to improve production efficiency and wafer yield Many reviews of these applications in the manufacturing industry have been reported and summarized, from which we can see most of the achievements related to DM application in manufacturing before 2015 [2,3,4,5,6], and many researchers have started to adopt the concept of Big Data [7,8,9,10,11] in smart manufacturing since . A comprehensive analysis of the reviewed literature from various points of view is provided subsequently, in Section 4, which summarizes data handling, discusses the DM with Big. Data application in different stages of the product lifecycle, and surveys the software used in these applications.
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