The Connected Factory concept is closely related to the Fourth Industrial revolution. A small digress into the emergence of this path breaking change(s) that are upon us will help us appreciate the potential impact on mankind.
The First Industrial Revolution (mid 18th to mid 19th centuries) introduced mechanized manufacturing spurring mass production in a few areas such as textiles. The Second Industrial Revolution (mid to late 19th century to the early part of 20th century) brought in ground breaking technologies such as the internal combustion engine while leveraging standardized delivery of energy (gas, electricity) leapfrogging large scale adoption of the factory concept for a wide variety of goods. A significant part of the world’s production today runs on the principles and thinking established during these revolutions such as mechanization to reduce human effort and error, and of course reduce the per-unit cost.
Both the ‘revolutions’ brought unprecedented (for the times considered) scale of change to mankind and were epoch making in their social and society impact with sustained changes in the way people lived, across the globe.
The third ‘revolution’ is recent (post World War-2/ mid 20th century onwards) and is also known as the ‘Digital’ revolution. Like the revolutions before, changes began slow, but very rapidly picked momentum and scale of change in each decade out-paced the changes and their impact in previous ones. Multiple advancements in electronics and miniaturization brought a positive spin off on telecommunications and computing capabilities led to scale-fold rise in computing power of machines (read computers) and compounded by established ability of machines to communicate through well established protocols (read this as the rise of the internet). Widespread automation and computerization of a breathtaking range of means of production, provision of services has replaced manual activity in multiple areas of commerce, and the interconnectedness has brought tremendous changes in the way people come together at all levels of society and governance. Never has mankind been able to interweave the lives of 2/3rd world’s population (see https://www.statista.com/statistics/269329/penetration-rate-of-the-internet-by-region/) and this has a far far reaching impact.
We are now in the age of Industry 4.0 (a term popularized by Klaus Schwab, executive chairman of the World Economic Forum, see The Fourth Industrial Revolution | Essay by Klaus Schwab | Britannica ), also known as the Fourth Industrial Revolution. This era builds on the achievements thus far and takes the capabilities of the factory floor way beyond mechanization & automation of tasks and communication of status. As per Wikipedia’s article, (paraphrased in this blog) this represents a fundamental shift in global design, production and supply of goods using modern smart technologies, large scale communication resulting in social, political and economic shift from the digital age of 1990’s and 2000’s that changes the ways humans experience and know the world around them.
At the core of Industry 4.0 is the Connected Factory. As the name suggests, this implies a seamlessly integrated manufacturing and supply chain setup using embedded technology, active sensors, industrial IOT’s and in turn using the power of computing (AI, ML, Big Data, Analytics) to understand and guide for productivity, reduced effort & cost, improved safety, meet environment needs. Each machine, each system and each component is built to sense, react and communicate. Smart sensors capture data and information in real time which is then integrated with the ecosystem, Machine Learning (ML) and Artificial Intelligence (AI) are leveraged to analyze, utilize and leverage this data and convergence.
Some key aspects of a connected smart factory:
Industrial Internet of Things (IIOT): IOTs designed for industrial use are a key ingredient in smart connected factories allows embedded sensors incorporated into machine design, as well as installation of external. They help connect data from machines and components to Cloud enabling control, deeper analysis and reporting. General Electric (Predix), Siemens (Mindsphere), Schneider Electric (Wonderware), Bosch, Fanuc (Field), ABB (Ability), Honeywell, and Cisco are some of the major names providing devices and control systems. In addition, several service providers have launched cloud based platforms to host and support IOT connectivity – Google Cloud IOT, Amazon AWS IOT, Oracle IOT Intelligent Applications, Microsoft Azure IOT, Cisco Kinetic IOT, PTC ThingWorx IOT, IBM Watson IOT, SAP Internet of Things.
Machine to machine (M2M) communication: Ideally, this is sharing and transfer of data and control between machines, without human intervention. This can happen directly between interconnected (mechanical, wired or wireless) machines or via servers that aid the consolidation and presentation of data. Transfer of control instigating robotic arm to pick up assembly for next stage without human oversight or intervention is a typical example . Real time data sync with a central control system (complex process industry applications such as chemicals, pharma, petrochem also multi-stage discrete manufacturing and assembly use in hi-tech electronics, automotive) is further enhanced by integrating with back end ERP systems for automated cost tracking, resource updates, inventory updates, shipment trigger, automated preventive/breakdown maintenance etc. Such connectivity is further enhanced by instant visibility in real-time control systems command centers and intelligence dashboards for operational and managerial use.
Mobile Applications : A logical extension of the connected factory is to improve the ability of human interaction with the factory. The last decade has seen an explosion of hand-held devices developed on both proprietary as well as open (such as Android, IOS) operating systems, that are light weight allowing freedom of movement to human operators, who no longer are tied to fixed-position control panels. Increasing computing power in the hand-held devices, as well as leveraging the capability of Cloud, has truly brought in MEC – Mobile Edge Computing / Multi-Access Computing to the fore. The devices can communicate with wireless protocols of BlueTooth, 5G (emerging protocol in mobile communications, a jump over 2G/ 3G/ 4G), NFC (Near Field Communication) as well as WiFi/ LiFi. These devices have dedicated applications and interfaces including exciting opportunities to leverage cutting edge VR (Virtual Reality) / AR (Augmented Reality)/ IR (Integrated Reality) as a means of sensing and controlling, visualizing, managing discrete pieces of machinery to entire lines on the manufacturing floor.
Cloud Computing: Applied in the manufacturing perspective, leverage of Cloud based resources and services (SaaS – software as a service, PaaS – Platform as a Service, IaaS – Infrastructure as a service and XaaS – Everything as a Service) for processing, analysis, storage and decision making at stages of product design through manufacturing & assembly stages to shipment. A manufacturer can focus more on core product and manufacturing than on non-core computing resources such as infrastructure, development & hosting, managing applications, using pay-as-you-go scalability for the non-core.
The National Institute of Standards and Technology (NIST) (a non-regulatory body of the US Department of Commerce) defines cloud computing as “a model for enabling ubiquitous, convenient, on-demand network access to a shared pool of configurable computing resources (e.g., networks, servers, storage, applications, and services) that can be rapidly provisioned and released with minimal management effort or service provider interaction.” (Link)
Cloud Manufacturing: This is an extreme illustration of the utility of Cloud where manufacturers can ask for services such as Product Design, stages of manufacturing, assembly and treatment, testing and certification, transportation – each from different Cloud based service providers. This allows radical re-thinking of the connected factory, including paradigms such as DAMA (Design Anywhere Manufacture Anywhere).
Big Data Analytics: The large number of IIOTs and smart manufacturing devices are designed to capture large amounts of information as data records. Much of this will be real time and online, utilized for active line and machine level controls and decision making. These large quantities and range of data from sensors and machines and devices constantly being loaded into Cloud, coupled with information from suppliers, quality control, production, maintenance, costing and financial can produce actionable insights leveraging the capability of Big Data Analytics to optimize manufacturing and management, improve accuracy of planning, improve efficiencies, cut costs, improve safety and productivity.
Task automation aided by smart sensors: So far, manufacturing automation and process control was implemented through stand-alone devices. These devices were able to pick up data on the fly, with some local storage which was used to result in prioritized and localized intelligent controls (example, if temperature exceeded 60 degC, switch on fan, if exceeds 80 degC shut down the rotor). In the connected factory, the emergence of cheaper and independent sensors and control units implies very high flexibility in data collection from an array of smart sensors, processing the data through Big Data Analytics combined with AI/ML to control the manufacturing device through multiple control units (example, if temperature exceeds 60 degC and rotor speed is above 1600 rpm and ambient airflow is less than 0.1 mtrs/sec, then brake the rotor and increase fan speed and increase louvre angles)
Advanced Robotics: Replacing humans with flexible and adaptable robots with consequent jump in overall accuracy, productivity and safety is possible with the new generation of advanced robots. While cost of labor has been increasing the last few decades, cost of robots and the associated software using plug and play has been falling rather steeply. It is now possible to imagine entire plants run by few humans with robots doing all the heavy lifting (pun intended). At the same time, it is now feasible using AI/ML to ‘teach’ robots to become better adapted to tasks as are the use of feedback loops for self-diagnosis and self-correction. ‘Cobots’ (short for collaborative robots) are designed to work alongside humans in versatile programmable tasks With rapid rise in modularity, robots need not be hardwired for a single task, but can be configured to meet the complexity, variety and cost of manufacturing process and assembly line requirements. Wireless mesh allow remote supervision and control of these complex devices
3D Printing: With the rise in size, capacity, quality and output of 3D printers (also known as additive manufacturing, since current technology ‘adds’ layers of material such as resin, fiber, plastic, ceramic, metal-composites even titanium and gold to produce intricate 3-dimensional shapes), it is now possible to imagine complete manufacturing lines designed around the capabilities of 3D printing. It is possible to implement remote offshore based units capable of replicating designs to high specifications. 3D printing allows for rapid prototyping, model building to produce items for ‘bridge’ manufacturing or to produce at scale. Using industrial grade 3D printing to quickly produce custom and unconventional fixtures, jigs and molds gives the manufacturer the ability to rapidly respond to demand variations, run experimental production lines, test market items, highly customized/ on-demand products and proof of concept items, usually at a fraction of weight and time to market. A celebrated case study circa 2016 shows Volkswagen (Link) saving 160k USD as a result of 3d printing of tooling alone. It is anticipated that the average cost of 3D printing technology will replace cheaper alternatives of non-smart injection molding in this decade.
Digital Twins: Digital twins are created as a representation of a part or whole to provide either
a) a physical replica of the real world system or model embedded with connected sensors to collate data under different stresses and environmental changes
b) a digital simulation of real life processes, systems and machines that help operators simulate and study operations and problems
Digital twins allow for quick and dirty as well as detailed and in-depth analysis of real life problems simulated in a virtual world, thereby limiting hazards, damage, costs and of course physical effort. It is possible to leverage Digital Twins to identify areas to improve efficiencies and plan for future improvement opportunities. The models can be updated at lower cost to keep them current with ongoing wear and tear, defects and sustained loading capabilities. When merged with historical data from real life systems, the simulated data from twins allow for richer, near real-time and massive simulation and iterative studies to be performed.
Conclusion Connected Smart Factories have revolutionized manufacturing and are here to stay. The convergence of several technologies is an inflexion point, and the disruption caused by this brings a quantum jump on several dimensions with positive rub-off on the satisfaction levels of existing customers (produced quicker, higher quality, more variety) as well as new ones (brought upon by ability to produce new products, services and address new markets bringing in new customers at scale).
a) Produce more quantity and quality: Ability to produce in less time (fewer setup/operations changes) with less human intervention (read reduced cost and improved safety) and higher quality (due to lower failures and closer tolerances of high-tech sensors)
b) Realtime control: Organizations can now head closer to the single-unit-batch of the Kanban golden pull system by responding to environmental and customer changes in near real time basis, allowing for higher variations with reduced risk
c) Run longer, run smarter: Longer operations runs not constrained by human fatigue or legal constraints of shift timing leads to more efficient utilization of resources
d) Run safer: One significant area of contribution is more control in hazardous manufacturing conditions that can now run on minimized or no routine human presence onsite.
e) Massively increased visibility: Connected systems as a result of the conjoined communication, cloud and big data are simply more visible to operations and senior management consuming the analysis and intelligence off the line
f) Greatly increased traceability: Up-and-down the supply chain, it is now possible to track and trace produced lots, batches and serial numbers.
g) Diagnostics and fault tolerance: Introduction and placement of sensors allows for instant identification and addressing of hot spots leading to better fault tolerance. With big data analytics using ML, early addressal of issues leads to longer life of machines as a virtuous cycle.
h) Flexibility: Routing controls, adaptability of 3D printing, mirroring by digital twins all lead to more flexibly automated lines that can produce a richer mix of products
i) Trickle down: New technologies evolve startups and establishment of new industries, leading to 3rd party services by local populations. Reduced dependence on training and skilled manpower resources can lead to use of remote locations for establishing large factories. All this leads to a trickle-down impact on local economies.
Industry 4.0 and connected smart factories bring in exciting times and many of us will experience the impact at first-hand.
Industry 4.0 (a term popularized by Klaus Schwab, executive chairman of the World Economic Forum, see The Fourth Industrial Revolution | Essay by Klaus Schwab | Britannica, https://www.britannica.com/topic/The-Fourth-Industrial-Revolution-2119734)
2/3rd world’s population now connect to the internet: see https://www.statista.com/statistics/269329/penetration-rate-of-the-internet-by-region/)
Wikipedia’s article on 4th Industrial revolution (Link: https://en.wikipedia.org/wiki/Fourth_Industrial_Revolution)
The National Institute of Standards and Technology (NIST) (a non-regulatory body of the US Department of Commerce) defines cloud computing as “a model for enabling ubiquitous, convenient, on-demand network access to a shared pool of configurable computing resources (e.g., networks, servers, storage, applications, and services) that can be rapidly provisioned and released with minimal management effort or service provider interaction.” (Link: https://www.nist.gov/publications/nist-definition-cloud-computing )