In the world of Industry 4.0., smart factories are no longer a thing of the future, but a present reality that some companies are counting on to get — and stay — ahead of the pack.
“Manufacturing is undergoing a technology-enabled transformation as businesses seek to increase competitiveness, efficiency and responsiveness in a global business landscape,” says Abby Jenkins, Product Marketing Manager for Oracle’s NetSuite. “The smart factory is at the core of that transformation.”
According to Deloitte, in five years, 86% of manufacturers believe smart factories will be the “main driver of competitiveness,” and 83% believe they will “transform the way products are made.”
“Smart factory manufacturing solutions can be architected across an array of enabling technologies,” Deloitte says. “They can create insights and augment human performance to help overcome complex challenges, address key business objectives, and boost visibility and performance across the digital supply network.”
Although experts tout the many benefits that smart factories offer, deploying them may be easier said than done — as noted by Gartner’s recently-released list of top five risks related to smart factory implementation.
Here, we’ll take a look at various smart-factory dynamics — including Gartner’s recommended strategies for mitigating those risks.
What is a smart factory?
SAP, a market leader in enterprise application software, defines a smart factory as a “cyber-physical system that uses advanced technologies to analyze data, drive automated processes, and learn as it goes.”
“Smart factories and smart manufacturing are part of the technological transformation known as Industry 4.0 or the Fourth Industrial Revolution,” SAP explains. “Each of the first three industrial revolutions was born out of an innovative new technology that completely changed the way we worked and manufactured goods: namely, the steam engine, the assembly line, and the power of the computer. Today, the fourth revolution is driven by digital transformation and intelligent automation.”
SAP points out that although manufacturers have been using advanced technologies for many years, the smart-factory difference is enabled by its interconnected nature.
“The people, assets, and data management systems in a traditional factory all operate in isolation from one another and must be manually coordinated and integrated on an ongoing basis,” the company says. “A smart digital factory works by integrating machines, people, and Big Data into a single, digitally connected ecosystem.”
SAP also notes that in addition to curating and analyzing data, a smart factory “actually learns from experience.”
“It interprets and gains insights from data sets to forecast trends and events and to recommend and implement smart manufacturing workflows and automated processes,” SAP explains. “A smart factory undergoes continuous procedural improvement to self-correct and self-optimize – it can teach itself (and humans) to be more resilient, productive, and safe.”
Types of smart factories
According to Oracle’s Jenkins, there are four types— or “levels” — of smart factories, which represent “successively higher degrees of data integration, analysis and automation.” She says they include:
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Basic data: Although data is available, it’s siloed within individual systems. As a result, manual processes are needed to combine data from disparate systems for analysis.
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Proactive data: Data is gathered and combined in a “structured database or a data lake” on a continual basis, which makes it possible to analyze it more efficiently. However, manual efforts are still needed for data interpretation.
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Active data: By using machine learning and AI, data can be automatically analyzed and patterns identified. “The system can start to analyze trends and anomalies — such as product defects — without human input. By analyzing data over time, the system can also start to make predictions and recommendations. …”
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Action-oriented data: Based on the insights and recommendations made by machine learning and AI processes, the manufacturing system can take action automatically — which typically requires it to have gathered “an extensive amount of data” previously “that enables it to understand the impact of changes it makes.”
Jenkins says the various technologies used in smart factories include:
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Industrial internet of things (IIoT)
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Virtual reality (VR) and augmented reality (AR)
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Big data and analytics
Benefits of smart factories
Among experts, the detailed list of smart-factory benefits could be a long one. SAP summarizes the potential benefits of digitization and smart factory use within three major categories:
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Productivity and efficiency: “…Smart factory technologies are designed to reduce the need for reactive practices and move supply chain management into a more resilient and responsive mode. …”
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Sustainability and safety: “…Modern smart factory technologies make it easier than ever for businesses to identify and implement opportunities for more green, safe, and socially responsible manufacturing practices. …”
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Product quality and customer experience: “…In the smart factory, cloud connectivity and end-to-end visibility in smart factories bring real-time insights and recommendations to all tiers of the manufacturing process. The ability for rapid customization and response to shifting trends means that products are tightly up to date with customer desires. …”
Jenkins says smart factories play a “central role” in manufacturing’s digital transformation.
“Advances in manufacturing technology — from cloud computing to AI and machine learning — enable dramatic operational improvements in areas such as manufacturing flexibility, product and process development, quality control and decision-making,” she says.
“The business benefits include increased productivity, improved efficiency and the ability to respond more rapidly to changing market demands. In turn, those advantages help growing companies succeed in an intensely competitive global environment.”
The following video demonstrates how electronics manufacturer, Pegatron, is using NVIDIA AI and Omniverse “to digitalize their factories so they can super-accelerate factory bring-up, minimize change orders, continuously optimize operations, and maximize production line throughput – all while reducing costs.”
Source: NVIDIA on YouTube
Smart factory challenges
Although many leaders are counting on smart factories to help optimize business processes, Gartner says the challenges associated with implementation are often underestimated:
“Successful smart factory initiatives require accompanying cultural and operational transformations that are slow by nature and in many cases will require entirely new organizational designs to integrate the new capabilities within the broader supply chain.”
Gartner says its research has identified the top five risks that should be avoided when new smart factory initiatives are launched — and offers strategies to mitigate them.
Risk #1: Confusing factory optimization with business model transformation
Contributing dynamics: “…When smart factory initiatives are disconnected from the rest of the supply chain, the site level benefits can come at the expense of creating costly constraints elsewhere in the business.”
Mitigation strategy: Ensure factory objectives “are synchronized with supply chain operating models and enterprise digital ambitions, flexibility and automation opportunities.”
Risk #2: Overlooking the scope of change management
Contributing dynamics: Although acquiring new technology may seem to be “straightforward and relatively cheap,” companies that underestimate the “resulting changes to existing processes, integrations and new performance targets” may incur higher time and cost requirements.
Mitigation strategy: Treat related changes as “part of an enterprise-wide initiative that requires alignment between senior leadership and the utilization of continuous improvement teams to ensure initiatives are properly sequenced.”
Risk #3: Underestimating the complexity of aligning and converging IT, OT and ET
Contributing dynamics: Smart factory governance is “not just centered on plant-business connections but also on how IT, operational technology (OT) and engineering technology (ET) are managed. These three are inseparable, and their convergence and alignment are critical as production models change.”
Mitigation strategy: “…supply chain leaders should familiarize themselves with alternative organizational models for IT/OT alignment and evolve governance and organizational structures in line with new production models.”
Risk #4: Insufficient funding for upskilling, reskilling and talent development
Mitigation strategy: Modernize learning and development (L&D) programs to “help associates learn, acquire and retain knowledge to acquiesce to new experiences…” and enable employees to “execute the work they are aligned to support through additional education and upskilling.”
Risk #5: Narrowly focusing on a single use case and technology
Contributing dynamics: With advances in technology, new tech solutions are continually available. Organizations that focus too much on “enabling technologies and the ‘art of the possible’” can find themselves facing “significant IT backlog and technical debt.” Gartner notes that these dynamics are complicated by the lack of a “single dominant technology or vendor that fulfils all smart factory requirements.”
Mitigation strategy: Balance technology purchases between “strategic considerations such as the ability to scale, along with the pragmatic, such as planning appropriately for operational disruptions.”
“Smart factory operations hold the allure of numerous benefits for supply chain leaders, from expanding lights out manufacturing capabilities to improving quality and solving labor challenges,” said Simon Jacobson, VP Analyst in Gartner’s Supply Chain Practice in a statement. “The potential for transformational benefits can also present the biggest pitfall, as organizations may rush into launching smart factory initiatives without a clear understanding of the extent of the challenges facing them.”
