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Data mining applications in engineering design, manufacturing and logistics

The volume of data grows at an unprecedented rate, in particular in the fields of scientific data, design and manufacturing, logistics engineering, medical, marketing, and financial data. Data mining offers tools for analysis of large databases and discovery of trends, patterns and knowledge. Since the first IEEE Data Engineering Conference in 1982, at least four data mining related journals have been established. Data mining is entering many applications in engineering design, manufacturing and logistics engineering. Numerous books have been dedicated to these applications. While many data mining papers have appeared in largely theory-based publications, journal issues discussing applications of data mining in engineering design, manufacturing and logistics engineering are rare. This special issue attempts to fill this coverage gap. It focuses on the theory and applications of data mining, text mining, web mining, and image mining in engineering design, manufacturing, and logistics engineering. The process of editing this special issue was guided by the principle that the papers must be of the highest quality, offer new contributions, and be relevant to the practice and further research and development of production systems. Therefore, all papers have been reviewed at least twice by at least two outstanding researchers in this field. Two principles were followed to avoid conflicts of interest in the review process. First, papers submitted by the guest editors were seen by the journal Editor, John Middle. Second, the papers were reviewed largely by reviewers outside of the pool of authors. As a result, some authors have not been assigned any papers to review, while many papers were reviewed by professionals who did not submit papers to the special issue. We have received papers from the following regions: Canada, China, Israel, Italy, Japan, Taiwan, United Kingdom, and the United States. Table 1 illustrates application areas of the accepted papers.