Building A Smart Factory

From Automation to Autonomy

About ten years after entering the global manufacturing sector's consciousness, Industry 4.0 seems to have lost much of its novelty. Its principles, technologies, market drivers, and national government policies have become known quantities. Smart factories, the intelligent, hyper-connected production plants that lie at the centre of Industry 4.0, have become detailed analysis and development objects.

Analysts predict robust future growth for smart factories and their contributions to global economic growth. Within the next five years, the study claims, intelligent factories will contribute up to $500 billion in value to the worldwide economy.

Analysts now look to smart factories producing more goods and services at lower costs as the source of these gains. Manufacturers predict that by 2022, smart technologies will drive a sevenfold increase in annual efficiency gains. The report indicates that with smart technologies, some industries will nearly double operating profits and margins.

Whether one believes that the oversized benefits these and other reports describe are believable, smart factories' global manufacturing growth is a real trend, one worth another look.

Big changes in the global manufacturing sector

Global manufacturing operations have undergone tumultuous times. Under the globalisation, developing economies joined the global manufacturing value chain and fulfil the work at the lower end of the supply chain, while first-tier manufacturing nations stay at the higher end. The system has proven to be vulnerable that in a case of a choking recession cutting off market demand due to unpredictable event like COVID-19, manufacturing verticals and employment will face a severe tumble.

Through all these difficulties, manufacturing activity remains a critical part of developing and technologically advanced economies. Manufacturing provides a path to better incomes and living standards. In developed economies, manufacturing still provides a vital source of competition and innovation. It is a significant source of exports, research and development, and productivity growth. A good example is Germany, whose 47% of GDP made up of manufacturing and its 27% of exports to the UK are vehicles.

The global manufacturing sector changes, bringing challenges and opportunities to manufacturing businesses of national and regional economies. However, business leaders or policymakers should assume future success based on old habits. So, what can one say about the future?

Manufacturing in the future

As nations mature economically and technologically, manufacturing is part of essential shifts in national societies. In a 2018 report, the McKinsey Global Institute clearly describes how manufacturing adds to the global economy. Some of its key ideas include:

Manufacturing's changing role. In advanced economies, manufacturing drives productivity, innovation, and trade more than employment and economic growth. Manufacturing in these countries has also started to use more services rather than relying heavily on making and selling their products.

Currently, manufacturing adds 14 per cent to global employment and 16 per cent to global GDP. However, the sector's relative size in a national economy varies with its stage of development.

In industrialised economies, they drive manufacturing output and employment growth. However, when manufacturing's GDP segment peaks at 20 to 35 per cent; it falls in an upside-down U pattern. As wages rise, consumers will spend more money on services. The service sector's growth accelerates, making it more important than the manufacturing industry as a source of improved GDP and employment.

(Source: United Nations and World bank https://www.statista.com)

Renew understanding of manufacturing's role. The manufacturing sector is also changing in other ways. Traditionally, manufacturing and services have been viewed as different sectors. This view is outdated. From advertising to logistics, services add up to a more significant part of manufacturing activity. In a year, every U.S. dollar of manufacturing output includes services worth 19 cents. More than half of employees have moved to service industries in some high-tech and engineering industries, such as office support staff and R&D engineers.

In the future, however, the manufacturing share of employment will continue to decrease. The drivers for such trend include long-term productivity improvements, faster service growth, and a global competition faced. These powerful forces push developed economies toward specialisation in jobs that require increased levels of work skills.

Manufacturing is not monolithic

Each national manufacturing sector is unique. In some nations, work in specific industries is more labour- or knowledge-intensive. Some economies rely more heavily on transportation, while for others, being close to customers’ proximity is a critical part of manufacturing growth. The authors cite five general manufacturing segments in the recent McKinsey report and then measure how production factors determine where manufacturers will build up factories as part of their Go-To-Market strategies.

Production Factor of Manufacturing

US Census; HIS Global Insight; Organisation for Economic Co-operation and Development (OECD); Mckinsey Global Institute analysis

The largest segment by output (measured as annual gross value added) includes chemicals, autos, and pharmaceuticals. These industries rely heavily on R&D activity, global innovation, and the need to stay close to their customers. Next in size is regional processing. This segment includes printing and food & beverages. These labour-intensive trade goods are the smallest segment, with only 7% of worldwide value-added.

Hence, given the significant dynamics, the only way to understand global economic activity is to make a detailed analysis of each nation's manufacturing sector.

A new phase of uncertainty and active change

Global manufacturers might have significant new business opportunities. However, they must operate in an more and more uncertain economic environment.?Questions like ‘Who will be our customers?’ and ‘What do they want, and what will labour and other resources cost in the next ten years?’ will be constantly asked to the manufacturers themselves.

Expect the emergence of a new global consumer class and that most consumptions will occur in developing nations. This situation creates lucrative opportunities for manufacturers in emerging markets.

In developed economies, the demand for mass-produced products is shrinking. In contrast, customers want a wider variety of products, more personalised designs, and a specific after-sales service to the individuals’ preference. Based on such needs, a wide variety of new materials and processes, from 3-D printing to advanced robotics, indicate a greater demand and drive for more productivity gains.

These opportunities appear in a challenging economic environment though. In lower-cost labour markets, wages are rising quickly. Resource prices are volatile, and a coming shortage of high-skilled talent creates more financial risk than existed before the Great Recession in 2008-9. With COVID crisis, more manufacturers are seriously considering to mitigate the risk with technology-based transformation in both their operations and business models.

Policymakers in developing new approaches

To compete in this dynamic age, manufacturing companies must:

·??????Understand customers more. Companies must realise specific emerging markets and the needs of their existing customers.

·??????Develop agile strategies and production processes. Decision making speed is as essential as rapid-fire production methods. Customers are changing their minds about what they want to buy. And, they will support manufacturers who have what they want, when they want it.

·??????Be willing to make big bets on long-range opportunities. Growth via better efficiency is one of many routes to manufacturing success. Finding and acting on new business opportunities is another. Manufacturers must be willing and ready to make bets on long-term prospects. All these are absolutely high-pressure decisions - manufacturers must be willing to enter new markets or switch to new methods and models to run their business.?

·??????Approach production and marketing strategies in a subtler way. In the past 30 years, market activity shows that labour-intensive industries' behaviour almost always resembles low wages. Most of these business opportunities are drying up. More nuanced manufacturing strategies must balance factors such as the access to high-skilled employees or lower-cost transportation.

·??????Policymakers need to step in and help manufacturers compete globally. They should:

• ?Have a thorough knowledge of their manufacturing sector. They must set policy with a detailed understanding of the many industry segments that make a national or regional economy.
• Make education and skills development top priorities. Policymakers should understand that supporting critical enablers is the best way to support ongoing growth, exports, and innovation. Two necessary preferences for governments and businesses include education and skills development.

Policymakers should help manufacturers build their R&D capabilities by upgrading product design and data analytics knowledge and skills. Companies will need computer-savvy production operators and responsive managers who can run worldwide supply chains. Improving public education—especially mathematics and analytical skills—is another must-have capability. Policymakers must collaborate with industrial and educational institutions that skills learned in school fit the needs of employers.

Given this complex picture, it'll be helpful to look ahead and see what might go wrong.

Potential manufacturing pitfalls

Worldwide, manufacturing sectors are likely to continue growing, but expect obstacles to this growth. National and regional economies are getting more difficult to predict, and manufacturers face both external and internal challenges. Here are some problems in the manufacturing industry and potential solutions.

Forecasting the demand for products

Today, many manufacturers have difficulty forecasting demand for their products and services. The use of advanced reporting software could – to a certain extent - help them estimate how many items they should sell in the future. Without modern tools, manufacturers often fail to meet customer demand and lose revenue by either building up redundancy or falling short of the market needs.

Controlling inventory

Inventory management is another major challenge to manufacturers. Industry 4.0 concepts expand the scope of manufacturing beyond processes that occur in smart factories to logistical tasks in product design studios, testing labs, and warehouses. Nevertheless, many manufacturers, especially smaller enterprises, manage their inventory without automation or IT.

Manually checking stock is inefficient and prone to errors, leading to inaccuracies, shortages, overstock, and damages. Thanks to the help of automated software, however, inventory control has become much more straightforward. Automation - and artificial intelligence - based solutions provide different levels of intelligence and hands-off inventory tracking and management.

Improving process efficiency

Manufacturers never stop looking for effective ways to cut costs and make their processes more efficient. Factory owners often sacrifice the quality of their offerings to cut production costs. This approach can backfire and compromise their revenue when dissatisfied customers stop buying mal-manufactured products.

Increasing returns on investment (ROI)

Manufacturers always want to increase their ROI. Often, they increase their selling price of the products when the initial marketing investment gains the branding and secures market share. However, these methods aren't as effective as they once were, obviously when unpredictable economic conditions reduce consumer purchasing power, or disruptive competitors enter into the same vertical sector. To enhance their ROI, manufacturing companies must engage in short-term and long-term activities to increase their sales, improve their marketing strategies, and continue to control or reduce costs.

Addressing labour shortages

When countries suffer an ageing workforce, many national manufacturing sectors are facing labour shortages. Automation and robots can help fill the labour gap, but manufacturers still need the human capabilities to analyse and solve problems and manage production processes.

Adopting new technologies

New technologies such as Internet of Things (IoT) devices, data analytics software, and robots appear on the horizon every year. The variety and number of these products could overwhelm manufacturers by the sheer number of choices.?Often we hear the questions from the industries such as "Will implementing this technology be the right decision for my manufacturing business?” "Should I adopt new technology at all? If so, which ones should I invest?".

Getting the product-level details and finances right is just part of the picture. Manufacturers should also plan their Industry 4.0 readiness and related roadmaps before deployment projects begin.

Defining the 21st-century smart factories

Smart Factories (also known as Connected Factories) have many definitions. One way to define them is a group of technology innovations. When used together, these innovations support consolidated, connected, and flexible manufacturing processes. The processes run manufacturing, supply chain, and related back-office operations.

Smart Factories enable machines and people to make intelligent decisions, which result in automated or human actions. Some definitions include smart factories reaching "self-optimising operations." In these cases, the factory continuously adapts to demand and variations in supply and corrects processes that exceed tolerances.

Another reason to build smart factories is that employees responsible for monitoring and controlling production lines can do so remotely with less human attention. Factories can now adapt to the workflows in real-time by machines communicating with other devices and humans.

Smart factory functions

How would one recognise a smart factory? Usually, a Smart Factory will define by its core functions, which include:

·??????Digital connectivity across shop floor

·??????Intelligent automation and decision making

·??????Cloud-based data management and analytics

Digital connectivity: Smart factories use sensors and other devices to collect production equipment data and send to the Internet of Things (IoT) via specific protocols for storage and further analysis. The insights extracted from the data enable monitoring production, logistics, and product design processes throughout the shop floor facility and beyond.

This sensor-driven capability increases the awareness of what is happening at several levels of factory operation. For example, traditionally vibration sensors provide alarms that indicate when bearings, motors, or machines need to be shut down. Now the deep insights of the data pattern could enable predictive maintenance actions that avoid larger production problems that would occur if the abnormal condition were left unattended.

With smart sensors, factory staff members can work with suppliers, partners, and customers more effectively. These sensors and sensor-embedded devices can, in turn, connect to a global system of similar process systems and digital supply chains through the factory, warehouses, and offices.

Intelligent automation: This umbrella term includes advanced robots, machine vision, distributed control processes, and drone technologies. Industrial robots detect and avoid people and other unexpected obstacles as they work. Avoiding such common disruptions is a huge advantage that can prevent production delays and downtime. Ultimately, automation applies intelligence at the factory level and creates a dynamic production environment, which improves product quality and reliability. Automated processes also involve intelligent agents and other cyber-physical systems to operate more efficiently and distribute manufactured goods more quickly in response to market demand.

Smart equipment makes it possible to automate much of what is required to produce smaller-sized manufacturing runs. Minimising downtime for recalibrating and resetting equipment makes manufacturing more customisable and helps manufacturers respond more quickly to changing market tastes.

Cloud-based data management and analytics: The industrial Internet of Thing (IIoT) is the global network of internet-connected, physical objects, and devices used in the industrial environment based on cloud infrastructure. The IIoT enables these objects to communicate with each other and with nonindustrial, internet-enabled devices and systems.

Making factories smart

Facility-wide communications and the ability to use manufacturing data is what makes factories smart. New technologies are developing and converging to create smart factories possible.

Smart factories connect production hardware, processes, and humans with data provided by sensors connected to the Industrial Internet of Things throughout factories and beyond. By combining all parts of the production process, a manufacturer can streamline and speed up building and testing products across every platform.

In smart factories, all industrial assets are connected in the same facility and between production facilities. At each stage of production, sensors exchange data in real-time, and data analytics applications monitor operations to ensure ideal process performance.

The evolution of smart factories is trending towards data-based management cultures and fully autonomous operation. Developing independent operation requires that plant managers change their perspective from a go-it-alone, problem-solving culture to a monitor-and fine-tune process culture. This type of change is often overlooked and undervalued. Manufacturers need to expect current organisational structures to be a significant obstacle to attaining smart factory design and process goals.

Identifying the pillars of smart factories

In both concept and capabilities, smart factories go beyond the conventional definitions of automated plants. Industry 4.0 principles recognise nine key technologies, which manufacturers can use to improve many production processes.

Industrial Internet of Things

Manufacturers attach sensors to physical assets located on the plant floor and then connect it to the worldwide control and measurement devices. This variation on the IoT connects devices, machines, data management software, process optimisation applications, productivity software, and humans. The objective is to collect data that influences decisions (often in real-time), making production more efficient and making more accurate decision-making.

Augmented reality

Unlike the all-digitals of virtual reality (VR), augmented reality (AR) uses a device, such as a mobile phone or special eyeglasses to display real-world digital content. AR can display data, instructions, or holographic images, atop a user's real-world appearance of workstations, equipment, production lines, or warehouse locations. The manufacturing sector has several uses for this technology, including:

Safety training: Often, new employees don't know the equipment, protocols, and procedures used on the factory floor. Preventing safety problems makes it essential to provide new workers with training as often and soon as possible. Using AR devices enables workers to view layered text and other digital information, which helps them grasp the plant floor's events without stopping the production line or diverting resources.

Streamlined Logistics: In warehouses and fulfilment centers, most shipments and orders require manual checking. By automating these processes, AR reduces human error and saves money, time, and resources.

Maintenance: By using AR devices, maintenance crews eliminate guesswork and save time. Equipment information viewed through AR visors includes preventative maintenance schedules and documents the service history of each machine.

Cyber-physical Systems

Manufacturing design, production, and logistics processes create mountains of data. Cyber-physical systems are computer systems in which machines will design, controlled, or monitored by computer-based algorithms.?

System data create models, which reflect the physical aspects of product development and production processes in a virtual environment. Engineers use CPS models to simulate, test, and improve machine processes and settings before production starts.?The desired result: to reduce process downtime, reduce product development time and costs, and improve overall product quality.

Additive Manufacturing (AM)

Manufacturers are expanding the use of additive manufacturing (3D/4D printing) in their product design and production processes. It already plays a vital role in three key areas:

Product design: The flexibility of 3D printing technology helps design teams to develop complex structures and shapes.

Prototyping: Additive manufacturing supports agile development by providing designers with a quick, relatively inexpensive way to prototype products. Manufacturers can "fail fast" in a controlled environment and experiment with several models before choosing a final design. Prototyping accelerates design cycles and reduces production costs by avoiding expensive rework in actual production.

Low-Volume production: When manufacturers need to produce small quantities of products, the additive approach provides the fastest and the most economical manufacturing method.

System integration

In Industry4.0 systems, connectivity is the bedrock of integration. Currently, many manufacturing information systems are not operating in an integrated manner. With improved system integration, all aspects of a manufacturing company—machines, devices, humans, and cyber-physical systems—can become interoperable, within and beyond smart factory walls. Most importantly, the integration will create an agile manufacturing environment, enabling real-time process corrections and more responsive processes.

Cloud computing

As manufacturers use more information technology and share more information in smart factories, hosted computing services provide almost unlimited data storage and computing power. Cloud-based computing services also help manufacturers make computing more scalable, data more accessible, and data cleaner and safer to use.

Autonomous robots

Although genuine autonomy is still a goal, not reality, this class of advanced robots performs tasks that require capabilities between automated robots and human workers. In some ways, automated production robots design to work like humans, but they have the added ability to monitor and transmit data.

Cybersecurity

As digital connectivity increases, the risk of a potential cyberattack and data loss threat grow with it. Any security breach could damage several factory operations areas, from the supply chain to production to the company's loss of reputation. Companies must prepare and protect their information systems, sensitive data, and production lines from cyber threats.

Big data analytics

There are massive amounts of untapped data in the manufacturing industry, and factory owners are just beginning to learn how to use it. The common theme among all smart technology pillars is data collection and analysis. High-volume, high-speed data collection and research have been available for more than five years. Big data analytics, cybersecurity-related pattern recognition, and inventory control are just three of many ways that data analytics contribute to more efficient factory operation.?

Human talent, the tenth pillar

Industry 4.0 experts encourage manufacturers to look beyond efficiency and new business models. Their advice: invest in human talent as well as manufacturing infrastructure. Manufacturers should welcome data specialists to thrive in the approaching digital manufacturing environment and become a vital part of its long-term success.

Human talent also needs the support of new tools and practices. Decision-makers will need help to recognise business opportunities as well as work more efficiently. Dashboards and other data and analytical tools can help specialists clean, organise, and present massive volumes of available data.

?Smart Factory Benefits

After smart factory connectivity, sensors, and intelligent decision-making technologies are installed, configured, and tested, one question remains. Will manufacturing processes improve? Will adding smart manufacturing systems to fabrication and assembly fundamental methods make manufacturing more efficient and workers more productive?

Improved capabilities

Advanced capabilities lie at the heart of process improvements. These capabilities include:

• Streamlined data discovery and collection: Smart technologies automate data collection and provide advanced production data analytics. These capabilities help managers make faster, more informed decisions. In a smart factory, connecting operations technology and business systems enable manufacturers to measure their key performance indicators against their high-level business goals.
• Predictive maintenance: With better monitoring of data and devices, manufacturers can predict and fix maintenance problems before causing downtime or product quality issues. For example, sensors connected to machines or devices can send condition monitoring or repair data in real-time. This way, manufacturers can identify and fix problems much more quickly.
• Less waste, more accurate forecasts: When operations and enterprise systems are connected, manufacturers can identify waste and make more accurate forecasts. Managers get a better understanding of demand levels and supply chain problems. With this information, factory operators can avoid costs related to excessive inventory or unexpected production volume.
• A faster, more accurate view of supply and demand: Smart, connected systems help manufacturers understand their operations and data. In a smart factory, digital connectivity gives manufacturers a clear, complete, and accurate view of bottlenecks, machine performance problems, and other operational inefficiencies. With this data, manufacturers can adjust yields, improve product quality, and reduce waste.
• Delegating routine tasks to robots: Improvements in automated decision-making machines (robots) make it possible for humans to intervene less and less in production processes.

Benefits: Essential Process Improvements

The single, most essential benefit that smart factories provide is enabling their operations to do more—give leaner processes, more flexible product development, and more agile responses to technical and market changes. The advanced capabilities we describe above make these process improvements possible:

• Lower product design and development costs: 3D printing supports rapid prototyping and testing of new designs. By using agile development methods, manufacturers can use "fast fail" Agile methods to design and test new or upgraded products.
• Lower operations costs: Smart manufacturing provides greater data access across the supply chain by defining which resources are needed and when real-time data enables manufacturers to reduce overstocking costs or shortfalls. Smart processes shrink the volume of waste and avoid system downtime by supplying just the number of parts that are is needed, neither more nor less.
• Lower capital costs: Increasingly, smart factory design includes production systems suited to different setups or more than one task–a robot that can drill and weld, for example. Using versatile multi-task assembly machines with fewer chassis can provide significant CAPEX savings.
• Lower labour costs: Delegating some assembly, inspection, and decision-making duties to cobots and automated assembly robots can reduce total human effort and labour costs.
• More agile manufacturing: Using data analytics and embedded sensors, smart factory logistics systems automatically compare demand levels and production rates. By using this capability, manufacturers can control throughput and respond quickly to changes in market conditions.

Much of the value that these benefits offer depends on end-to-end connectivity and the interoperability that connections of the industrial Internet of Things enable.?