Page 18 - AeM_April_2022

RESEARCH, ANALYSIS & TRENDS

production problems that would occur if the abnormal tive from a go-it-alone, problem-solving culture to a
condition were left unattended. With smart sensors, monitor-and fine-tune process culture. This type of
factory staff members can work with suppliers, part- change is often overlooked and undervalued. Manufac-
ners, and customers more effectively. These sensors turers need to expect current organizational structures
and sensor-embedded devices can, in turn, connect to to be a significant obstacle to attaining smart factory
a global system of similar process systems and digital design and process goals.
supply chains through the factory, warehouses, and
offices. Identifying the pillars of smart factories

Intelligent automation: This umbrella term includes In both concept and capabilities, smart factories go be-
advanced robots, machine vision, distributed control yond the conventional definitions of automated plants.
processes, and drone technologies. Industrial robots Industry 4.0 principles recognize nine key technologies,
detect and avoid people and other unexpected obsta- which manufacturers can use to improve many produc-
cles as they work. Avoiding such common disruptions tion processes.
is a huge advantage that can prevent production delays
and downtime. Ultimately, automation applies intelli- 1. Industrial Internet of Things: Manufacturers at-
gence at the factory level and creates a dynamic pro- tach sensors to physical assets located on the
duction environment, which improves product quality plant floor and then connect it to the worldwide
and reliability. Automated processes also involve intelli- control and measurement devices. This variation
gent agents and other cyber-physical systems to oper- on the IoT connects devices, machines, data man-
ate more efficiently and distribute manufactured goods agement software, process optimization applica-
more quickly in response to market demand. Smart tions, productivity software, and humans. The ob-
equipment makes it possible to automate much of what jective is to collect data that influences decisions
is required to produce smaller-sized manufacturing (often in real-time), making production more effi-
runs. Minimizing downtime for recalibrating and reset- cient and making more accurate decision-making.
ting equipment makes manufacturing more customiza- 2. Augmented reality: Unlike the all-digitals of virtu-
ble and helps manufacturers respond more quickly to al reality (VR), augmented reality (AR) uses a de-
changing market tastes.
vice, such as a mobile phone or special eyeglass-
es to display real-world digital content. AR can
Cloud-based data management and analytics: The
industrial Internet of Thing (IIoT) is the global network display data, instructions, or holographic images,
of internet-connected, physical objects, and devices atop a user's real-world appearance of work-
used in the industrial environment based on cloud infra- stations, equipment, production lines, or ware-
structure. The IIoT enables these objects to communi- house locations.
cate with each other and with nonindustrial, internet- 3. Cyber-physical Systems: Manufacturing design,
enabled devices and systems.
production, and logistics processes create moun-
tains of data. Cyber-physical systems are comput-
Facility-wide communications and the ability to use
manufacturing data is what makes factories smart. New er systems in which machines will design, con-
technologies are developing and converging to create trolled, or monitored by computer-based algo-
smart factories possible. Smart factories connect pro- rithms. System data create models, which reflect
duction hardware, processes, and humans with data the physical aspects of product development and
provided by sensors connected to the Industrial Internet production processes in a virtual environment.
of Things throughout factories and beyond. By combin- Engineers use CPS models to simulate, test, and
ing all parts of the production process, a manufacturer improve machine processes and settings before
can streamline and speed up building and testing prod- production starts. The desired result: to reduce
ucts across every platform. In smart factories, all indus- process downtime, reduce product development
trial assets are connected in the same facility and be- time and costs, and improve overall product quali-
tween production facilities. At each stage of production, ty.
sensors exchange data in real-time, and data analytics 4. Additive Manufacturing (AM): Manufacturers are
applications monitor operations to ensure ideal process expanding the use of additive manufacturing
performance. The evolution of smart factories is trend- (3D/4D printing) in their product design and pro-
ing towards data-based management cultures and fully duction processes. It already plays a vital role in
autonomous operation. Developing independent opera- product design, prototyping, and low-volume pro-
tion requires that plant managers change their perspec-
duction.

18 April 2022: Marketing Automation: AI, Big Data & Deep Learning