Demystifying Smart Manufacturing: Three Things Smart Manufacturers Do Differently – and Better

Cloud Computing4 minutes readJul 8th, 2021
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No industry has been untouched by the surge of Big Data and the reach of machine learning (ML) and artificial intelligence (AI) in the past decade. The manufacturing industry, in particular, has moved swiftly from a product and supply chain-centric model – which emphasized adopting the right ERP models and fostering the right relationships – to a more complex “data-centric” model.

Through smarter data management, manufacturers can leverage relationships for maximum value and gain insight to make products that target customers better. As such, smart manufacturing (aka Industry 4.0) is now becoming an even newer goal standard for many medium and large manufacturing realities.

But what is smart manufacturing, and how can you benefit by employing its practices? Consider these three key areas that capture what a smart manufacturer does differently – and better:

1. Data is the new oil! – Recognize the importance of data:

  • Pull, link, and manage all data, fully digitalized, in one place, from customers to IoT, from supplier performance to operational technology (OT) data, to create “one version of the truth”
  • Move from analyzing historic patterns to predicting the future
  • Ensure that data is kept secure at all times and tightly control access
  • Cost-effectively deliver these capabilities and define ownership, governance and delivery models

2. Focus on smarter monitoring as well as on actionable insights:

  • Generate actionable outputs for every area of the firm:
    • Operations / logistics
    • Sales and marketing
    • Finance
    • Supply chain
    • HR
    • R&D
    • Customer
    • After-sales
  • Provide a way to cross-correlate all the above areas and effectively inform multi-discipline strategies to boost efficiency and effectiveness across the board (e.g., impact of R&D on customer profitability and experience)
  • Use complex dashboarding to view what is happening, adopts advanced analytics (AI and ML) to address issues, identifies agile recommendations, and optimizes the underlying manufacturing environment

3. Enforce future proof and sustainable ways to address technology advancements:

  • Cloud, either public or private, is a must
  • Invest in OT, not only in IT (e.g., IoT, sensors data technologies, image recognition)
  • Actively look into “alternative” technologies, such as blockchain
  • Learn from other industries where data is utilized for all stages of decision making and is kept highly secure
  • Enforce agility by deploying technologies that prevent shortcuts and workarounds

Smart manufacturing in action

How can you modernize your approach to operations to enable smart manufacturing? Consider the following examples of smart manufacturing in action:

  • Digital Twins – Provide a real-time digital counterpart of physical objects or processes throughout the company to ensure a holistic view of data and processes.
  • White Space Knowledge Map – Are you aware of all the skills in your company? Do you know what knowledge is documented and what isn’t? Knowledge graph-based solutions can help with these questions by automatically detecting knowledge items in your data, linking them together, and providing an analyzable representation of your knowledge.
  • Digitized, Data-Driven Workflows – Enable users to get their work done faster. For example, an AI-driven site inspection app can allow safety inspectors to document their work electronically.
  • Virtual Staff Assistance – Chatbots and augmented reality systems can assist employees with their tasks by providing easy access to a broad knowledge base. AI technology can help jump-start chatbot technology by automatically ingesting already available, unstructured content like documents from file servers, manuals, SharePoint data, or internet resources.
  • Predictive Maintenance – Intelligent monitoring of machinery through Industry 4.0 applications can reduce downtime and increase operational efficiency.
  • Supply Chain Analytics – predict illegal, unregulated and unethical supply chain activities.
  • Demand forecasting – Enable optimal staffing to manage both fixed and variable costs – even in pandemic times.

How Unisys can help

Unisys’ comprehensive and customizable managed services offerings accelerate digital transformation to enable smart manufacturing. Our solutions bring an upsurge of workstream collaboration that allows manufacturing workers to collaborate, access, and share information easily, quickly, and securely within the company ecosystem globally to address problems and create solutions.

Unisys’ digital workplace solutions for manufacturing are secure, easy for manufacturing employees to access and use, and offer consistent experiences across all devices and locations. As a result, Unisys’ clients can control costs efficiently while keeping the lights on, expanding and growing with artificial intelligence, machine learning, and leveraging virtual assistants for routine tasks.

Contact us to learn how Unisys can help your organization make the transition to smart manufacturing : https://www.unisys.com/contact-us.

Tags-   Artificial Intelligence Machine Learning Manufacturing smart manufacturing


About The Author

Markus Bertl

Markus Bertl, Data Intelligence and Governance Lead Architect for Application Services, focuses on data science, analytics, artificial intelligence, and emerging technologies to provide businesses with the tools to make use out of their data.

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