Abstract:
With the extensive development of new technologies and the application of information
in the manufacturing industry, immense volumes of distinct data are being generated and
collected daily. However, this data is largely unusable as its not meticulously cleaned and
processed. The effective utilization of such complex data is the cornerstone of data analytics,
as successful analysis leads to useful, relevant, and actionable knowledge, which in the long
run can prove to be revolutionary for any field and open new avenues. Although the application
of data analytics in areas such as sales & marketing, healthcare, cybersecurity, and climate
change is largely prevalent, the implementation of data analysis and its tools for efficient
product & process design is an unexplored opportunity with large volumes of data generated
by major stakeholders throughout the manufacturing and product-process design activity
remaining underutilized. This thesis, therefore, defines a novel conceptual framework that
applies data analysis to integrated product-process design (IPPD) for weighted data driven
IPPD that amalgamates data generated from multiple streams. Primarily from the user
perspective, supply chain network, current & upcoming technological processes, and
competitor process and product designs, will be utilized. The proposed framework can be
further used to create new products better aligned with customer requirements, enhance the
overall quality of the product, improve production efficiency through new technological
advancements, support the supply chain network, and give the applicant industry a competitive
advantage against its competitors
