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Data Science Center Tilburg

Setting the Stage for Smart Industries

DSCT Blog - December 2015 | Michael Papazoglou - Professor of Computer Science

Smart industries of the future & Data Science

Today traditional factories continue to operate as "black boxes" within very localized environments. They typically do not have adequate, timely status information on the external events that affect their own operations and costs. There is also evidence of increased distance between enterprise-level decision-making and the manufacturing plant floor, nor are factories able to easily exchange data with the supply chain. This promotes uncertainty that frequently results in manufacturing and supply chain inefficiencies.

Recent evidence from analyst studies on critical trends, challenges, and opportunities for manufacturing today reveals several alarming factors [United Nations 2014]1:

  • Most firms are optimizing their supply chains on a local basis (e.g., by function, facility, product, or geography) rather than seeking larger efficiencies by taking a global network view;
  • The focus of supply chain collaboration continues to be on the back end (with suppliers) rather than on the front end (with customers) where many of the biggest rewards await manufacturers;
  • Flexibility is getting more difficult as production chain activities grow more complex.

To address such problems smart industry (or smart manufacturing) solutions are introduced to enable manufacturing industries to enhance operational efficiencies, improve productivity (production speed, operating precision, energy and materials consumption), and drive economic growth. Smart industries are characterised by a combination of novel IT technologies (including software-driven services, Internet of Things (IoT) and Cyber Physical Systems), knowledge, processes, information, data analytics, predictive big-data capabilities and human ingenuity.

Smart industries will lead to industrial production of the future, which will be characterized by the strong personalization of products under the conditions of highly flexible (large series) production, the extensive integration of customers and business partners in business and value-added processes, and the linking of production and high-quality manufacturing services.

Smart industry is driven by the European Commission’s flagship programme Factories of the Future, The German Federal Ministry’s of Research – BMBF - multi-billion programme INDUSTRIE 4.0 (, and the Dutch industry’s Smart Industry initiative (

The Value Drivers of a New Industrial Paradigm

Smart industry capabilities are characterised by manufacturing “intelligence” which is expected to be commonplace and will be exceedingly utilised for the configuration of production systems, including their real-time control and monitoring. Manufacturing intelligence signifies the capability to:

  • provide enhanced and real-time manufacturing visibility, transparency, and analytical insights from shop floor events that are collected through sensor networks,
  • optimize use of dispersed, high velocity and volume data, resources (including devices and machines) and human expertise,
  • analyse and cross- correlate production data to manage production operations, and
  • plan a coordinated response to individual and collective manufacturing needs.

Prerequisite for smart industry capabilities is reliance on smart manufacturing technology and data science solutions that consider the “Holistic Factory” (smart, self-organized factory) and incorporate human factors to enable the integration of manufacturing knowledge with human behaviour and actions. These solutions are based on a flexible and end-to-end, timely and consistent representation of manufacturing data, knowledge and their interdependencies at all levels ranging from the manufacturing factory floor (where robots, devices and sensors reside) to the level of strategic decision-making. Furthermore, it involves collaboration between humans and machines, which will result in unprecedented levels of productivity and more engaging work experiences.

Resource efficient factories rely on advanced predictive analysis techniques and exploit the availability of vast amounts of production-related data, to manage critical events in the real time, propagate their impact on the subsequent factory processes and forecast the economic consequences, empowering adjustment as well as business and strategic actions.

Big data in manufacturing is characterised by huge data sets and varied data types (e.g., engineering and product images, text, and machine log files), which the production line is producing at a much faster rate than ever before. When this data is collected, integrated, curated and analysed, manufacturers can gain valuable insights derived from finding patterns for both product distribution and customer behaviours, extracting meaning, and ultimately making decisions that lead to greater efficiency and productivity while reducing costs. This could be accomplished by improving product quality, gaining real-time insights into root causes of manufacturing issues and even resolving them before they occur, thus increasing throughput, reducing machine failures and downtime. By taking advantage of growing data streams smart industry solutions apply powerful analytics for insights that can enhance existing services, enrich customer experiences and create alternative revenue streams, not only through new products but also through entirely new business models.

With smart industry it is expected that the nature of production itself will be transformed, driven by trends such as new forms of modelling and additive manufacturing through to pervasive computing, advanced software-driven service and sensor technologies and advanced robotics. Production will involve the integration of complex physical machinery with networked sensors and with software for big data analytics across the product lifecycle.

Thus, the factories of the future will be exceedingly varied, and more distributed than those of today. The production landscape will include mega-factory networks producing complex products; reconfigurable units integrated with the fluid requirements of their supply chain partners; and local, mobile and domestic production sites for some products. The academic and wider business community is in great need of the next generation of data scientists that can deal with the above multi-disciplinary challenges, embark on ambitious scientific yet industry-relevant programmes and help to make the grand vision of smart manufacturer a reality.

[1]   [United Nations 2014] United Nations Task Force on Global Production “Guide to measuring global production”, January 2014,