Authors:
Nadeem Iftikhar
1
;
Thorkil Baattrup-Andersen
2
;
Finn Ebertsen Nordbjerg
1
;
Eugen Bobolea
1
and
Paul-Bogdan Radu
1
Affiliations:
1
University College of Northern Denmark, Aalborg 9200 and Denmark
;
2
Dolle A/S, Frøstrup 7741 and Denmark
Keyword(s):
Industry 4.0, Data Analytics, Smart Manufacturing, Logistic Regression.
Related
Ontology
Subjects/Areas/Topics:
Artificial Intelligence
;
Business Analytics
;
Data Analytics
;
Data Engineering
;
Knowledge Discovery and Information Retrieval
;
Knowledge-Based Systems
;
Predictive Modeling
;
Statistics Exploratory Data Analysis
;
Symbolic Systems
Abstract:
Due to the emergence of the fourth industrial revolution, manufacturing business all over the world is changing dramatically; it needs enhanced efficiency, competency and productivity. More and more manufacturing machines are equipped with sensors and the sensors produce huge volume of data. Most of the companies do neither realize the value of data nor how to capitalize the data. The companies lack techniques and tools to collect, store, process and analyze the data. The objective of this paper is to propose data analytic techniques to analyze manufacturing data. The analytic techniques will provide both descriptive and predictive analysis. In addition, data from the company’s ERP system is integrated in the analysis. The proposed techniques will help the companies to improve operational efficiency and achieve competitive benefits.