The Digital Manufacturing Landscape and the Path Forward.

Any discussion on digital transformation and IoT leads to the fundamental question – “What are the possibilities and impacts in my industry?” The manufacturing industry has been dealing with this question for the last 50 years and in fact, has been an early adopter of technology to enable transformation.   For example,  in the mid-to-late 20th-century, automated inventory control systems (ICS),  material resource planning systems (MRP), and  enterprise resource planning systems (ERP) had a tremendous impact on the foundational operations within manufacturing across the world.  Then in the later part of the 20th-century and the early part of 21st-century transformations within this industry were enabled by the emergence of the PC, explosion of the internet, realization of e-business, availability of IP-based technologies, universal  adoption of RFID and proliferation of wireless components.  All of these innovations marked the first era of digital manufacturing.  This era had a primary focus on using technology to achieve efficiencies, effectiveness and productivity gains particularly within the supply chain, and product lifecycle management functions.

Digital Manufacturing

Today pioneering and prominent manufacturers are looking at the next generation of digital manufacturing which will utilize technology to enable new customer experiences that enhance profitable revenue growth. The German government is credited with calling this next era Industry 4.0. They characterize this era as a time when “people, machines, and industrial processes are intelligently networked.”

In a March 2015 article, a team of McKinsey Quarterly authors position this transformation as “Digitizing the value chain,” where the value is obtained by “connecting individuals and machines in a new digital thread across the value chain.”  This next era represents a fundamental change to enabling capabilities and systems that will be built and deployed for interconnecting people and things versus just interconnecting systems in the previous era. Representative examples into what is being done today include:

Process improvement – Operations teams having the ability to access real-time information on the process, inventory, and order status by integrating and automating business processes.

Quality control – R&D teams and product design teams interacting in real- time with shop floor employees to achieve a high level of quality control.

Product development – Use of embedded, sensors, actuators and digital identification tags within production lines and products being used in the field by customers to provide greater insight into methods to improve product quality.

Supply chain execution – Operations managers can connect and automate data flow in real time across an ecosystem through cloud-based platforms that provide secure access and data exchange.

Notice in this era, the attention becomes technology associated with data, analytics, processes and interconnections involving people and devices across an ecosystem. This approach will require the integration of business systems, IT – OT systems and end products, which will enable new capabilities and interactions. It will force those involved in the manufacturing ecosystem to change their thinking around automating in-plant processes to include a broader ecosystem of partners, customers, competitors and adjacent industry enablers. Product lifecycle management and requirements engineering processes will change to include new ways to collaborate and crowdsource to modernize product development, product support, product maintenance and warranty management.

Software Platforms

The path forward to the era of Industry 4.0 will be based on the successful use of ecosystem enabling software platforms.  These software platforms change how data is aggregated from disparate data sources, analyzed to identify patterns and then utilized as part of automating process execution to allow enhanced ecosystem interactions and transactions.  The appeal of these platforms will be on access and collaboration versus acquisition and ownership.  The results that can be obtained include flexible value chain orchestration, environmentally friendly facilities and greater responsiveness to customer needs across the value chain.

For more information visit: http://www.cisco.com/go/analyticsautomation

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