Wednesday, February 10, 2016

How to Achieve Smart Manufacturing

By Conrad Leiva, MESA International Board Member and chair of MESA's Smart Manufacturing Working Group

This article was originally published on IndustryWeek IdeaXchange ( on Dec 31, 2015.

For more information on Smart Manufacturing, if you are a member, check out the white paper "Smart Manufacturing - The Landscape Explained".
In the 1970s and 80s we witnessed a revolutionary wave of productivity improvements in manufacturing. New technologies, including personal computers (PCs), numerically controlled (NC) machines, programmable logic controllers (PLCs), and computer aided manufacturing (CAM), combined with new process improvement ideas like Total Quality Management (TQM), Just-In-Time, and Six Sigma yielded new levels of productivity and efficiency in many manufacturing industries.  
In this decade, we are seeing a convergence of technologies and process improvement initiatives of a similar scale with the potential to radically improve the way manufacturers thread processes and systems in the enterprise and the way they deliver customization and services to customers.

The building blocks for Smart Manufacturing

Organizations that bring together manufacturers, technologies and information systems, like the Manufacturing Enterprise Systems Association (MESA), the Industrial Internet Consortium (IIC), the Digital Manufacturing and Design Innovation Institute (DMDII), and the Smart Manufacturing Leadership Coalition (SMLC), are working on initiatives including the Industrial Internet of Things (IIoT) and Smart Manufacturing to coordinate this convergence of technologies and realize the process improvement potential sooner rather than later.
Smart Manufacturing is an initiative to bring about a revolution in manufacturing business strategy, turning traditional factories from cost centers into profitable innovation centers, through the integration of industrial automation, IIoT, and information technology (IT) including cloud services, 3D models, mobile computing, intelligence, and integration platforms.

Smart Manufacturing initiatives include the following goals:
  1. Achieve new levels of efficiency to support new services and business models including mass customization (highly configured products) and product-as-a-service.
  2. Ability to receive published data from equipment using secure open standards, analyze and aggregate the data.
  3. Provide data from connected manufacturing equipment and processes directly into new analytics and event triggering capabilities into systems of record and process workflows that can loop back and trigger programming, tuning  or maintenance changes on connected equipment.
  4. Enable more autonomous and distributed decision support at the plant floor level as smart machines are equipped with their own processing abilities and connectivity to enterprise systems.
  5. Promote the use of machine-to-machine (M2M) and application-to-application (A2A) connectivity standards in order to make these advanced capabilities accessible to manufacturers of all sizes and in all industry sectors, at acceptable levels of cost and implementation complexity.

To achieve the above goals for the Smart Manufacturing revolution we are counting on the following building blocks:

  1. Smart machines and advanced robotics Smart machines communicate with manufacturing systems and display a high level of autonomy. These machines recognize product configurations and diagnostic information, and make decisions and solve problems without human intervention. Robots with enhanced sensors, dexterity and intelligence can perform tasks without being pre-programmed as they can learn from experience. Sensors make them aware of the environment and safer for the people around them.
  2. Industrial Internet of Things (IIoT) – Manufacturing devices with network and internet connectivity– from mobile tablets to smart shelves to sensors embedded in automation controls to smart machines – are all active participants in event-driven self-tuning manufacturing processes integrated with open standards that support connectivity via the internet.
  3. Enterprise integration platforms - Enterprise integration platforms, like Enterprise Service Buses (ESBs), Manufacturing Service Buses (MSBs), and API Managers, have the ability to receive data broadcasted from equipment via secure open standards, analyze and aggregate the data, and trigger process controls and business processes across the enterprise.  Internet cloud services enable new connection capabilities across the enterprise and into the supply chain.

As an example, imagine a process where (a) RFID tags embedded in products broadcast the product configuration information to machines, (b) automated parts placement, assembly and inspection machines switch programs based on the received product information from each unit, (c ) defective product is routed out of the regular assembly line to a rework station, (d) defect information is messaged to the integrated enterprise quality system, and (e ) materials are ordered based on consumption reported by machines and delivered to the machine via automated material handling equipment.

Connected cognizant resources and systems drive automated processes in the Smart Manufacturing plant

However, there are some challenges on the journey and organizations are working on Smart Manufacturing initiatives because we are still falling short in some areas to achieve the desired levels of connectivity in manufacturing processes.

If we want these solutions to be broadly available to small and medium size manufacturing companies, we will need to work on the following areas:

  1. Broad adoption of machine-to-machine (M2M), application-to-application (A2A), and business-to-business (B2B) integration standards that will enable multi-vendor hardware and software plug and play solutions with open integration platforms to the internet. Organizations like ISO, IEC, NIST, and OAGi play a key role in establishing and promoting standards for connectivity.
  2. Data messaging standards that create a digital thread of communications from product definition in engineering systems to manufacturing and inspection processes. Standards that not only distribute the product 3D definition but also communicate changes and record production history for traceability and archival purposes.
  3. New workforce skills will be required for the smart factory. Workers will need to learn how to configure and maintain smart machines and robots. IT personnel will need to learn about manufacturing systems, protocols for equipment integration, and how manufacturing data flows into business intelligence and corporate metrics.  

To accelerate progress on the Smart Manufacturing revolution, organizations can work towards resolving the above gaps. To be on the forefront of adoption and a step ahead of the competition, organizations can get involved with some of the initiatives and organizations listed in this article.

For more information on Smart Manufacturing, if you are a member, check out the white paper "Smart Manufacturing - The Landscape Explained".

About the author:

Conrad Leiva
VP Product Strategy and Alliances

Conrad’s career has included consulting with many Aerospace & Defense companies on how to streamline the paperwork and information flow among Planning, Inventory, Quality, Production and Supply Chain disciplines. Recently, his work has focused on manufacturing intelligence and the integration between engineering, business, and manufacturing systems working with PLM and ERP partners. Conrad is VP Product Marketing and Alliances at iBASEt. Conrad holds an M.S. in Industrial Engineering from Georgia Tech, certification in MES/MOM manufacturing operations management methodologies, and is a certified quality auditor.

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