The global recession in the last few decades has had a significant impact on the way industries operate. The recession has forced industries in the manufacturing sector to undergo a fourth industrial revolution, commonly referred to as Industry 4.o.
This industrial revolution is mainly in a bid to cut on labor costs that keep on surging. The answer to the labor intricacy is solved by incorporating automated systems and Information Technology (IT) solutions in manufacturing industries. Automation is largely dependent on Information Technology. With automation, a process that would have typically required several people to handle is currently monitored and controlled from a computer screen and, in some cases, from mobile devices.
Automation of manufacturing industry
For many manufacturers, automation is the key to efficiency and eventual cost-cutting. Automation is not by itself the only tool, but others like robotics are performing above expectations, and at the lowest cost in the long run.
Automation encompasses three main components, i.e., machines, their computer-controlled programs, and the operators (human beings). These three components are the basic foundation of the internet of things (IoT) that controls connected devices from a central point.
Automation in manufacturing is most important inside the factory floor or the plant. Here, automation involves mechanizing process steps in such a way that the required product is made without involving humans.
Based on the end product and the steps to be followed, automation exists on different types and levels. The available or the needed machines and resources play a vital role in the type of automation to be employed.
Processes that are commonly automated include welding, packaging, painting, and food preparation. These tasks require data collection, analysis, and interpretation, which is efficiently handled by the computer. Control systems collect and relay data to the computers from where processing takes place. For each problem in manufacturing, there is an IT solution.
Below are the most common types of automation and their most common applications
1. Fixed automation
This is where a simple application is utilized alongside pre-programmed instructions. Such an assembly is relatively fixed and cannot adjust to modifications in product design. To make the best out of this type, the purpose must be a single one.
Where it is used:
- Transfer lines
- Automated goods and materials handlers
- Mechanized assembly lines
Advantages of fixed automation
- Minimal cost per unit
- A high rate of work
- May not readily accommodate different products
- The machines are highly prone to failure
- High initial capital investment
2. Programmable automation
Just as the name suggests, programmable automation allows for continuous changes in the product. For that reason, this automation is best practiced by manufacturers producing goods in lots or batches. The system constitutes a physical system and a program. Making something new requires a program written for that product. Manufacturers change programs only, or variables, but the system remains the same.
This automation type is being rapidly adopted in developing countries and promises even a bigger global footprint.
Where it is used
- CNC (Computer Numerical Controlled) machines and lathes
- PLC (Programmable Logic Controller)
- Industrial robots
Advantages of Programmable automation
- Can produce various designs of the same product depending on the program issued
- Good for production in batches
- Slower in production than fixed automation
- Heavy initial capital investment
3. Flexible automation
This type of automation is like an advancement of the programmable type. A manufacturing line using flexible automation can produce a range of products, and with no time wasted, when changing from one product to the other. Flexible automation does not only save on time that would otherwise be required for reprogramming but can also be scheduled such that different batches can be made without even switching programs. This is the main difference between this automation type from the programmable type.
Where it is used
Advanced robotic arms can do tasks such as drilling holes and insert rivets or screws. Such a flexible arm can also spray paint. A good example is the company Tesla that produces electric cars. Most of their work is done by such robots, although they still use other automation methods.
Advantages of flexible automation
- Produces different products continuously
- Can handle various designs of products
- Medium rate of production
- Requires a large initial capital investment
- Higher cost per unit of product made, compared to fixed automation.
There is another less popular automation technique known as Totally-Integrated Automation (TIA). It was introduced by Siemens Automation and Drives. The main feature of TIA is the use of a common software environment, communication method, and data management system. This feature makes it applicable in many unique industries such as plastic processing and 3D printing, automotive, packaging and manufacture of general, specialized, and other mechanical equipment. Food processing industries are also embracing this automation, proving the prowess of IT solutions for manufacturing.
Advantages of TIA
- Higher investment security
- Use of common resources lowers its complexity
- More productivity
- A short time to produce means a reduced time-to-market time
- High capital investment
There are other things that IT in manufacturing has facilitated. Smart mobile devices are very common and convenient. Equipment manufacturers are developing mobile applications that can monitor an entire plant. This information can reveal any problems in the plant, thus saving on the maintenance cost, time, and labor.
IT has accelerated the process of automation in the last two decades more than ever in human history. For manufacturing industries, this is a two-sided agenda. Amid the numerous benefits, these are some negative results of the so-called 4th Industrial revolution:
- Reduced employment
- The sudden change of work roles
- The operators and the general workforce need training and continuous learning especially if dealing with flexible automation systems.
With automation, comes other needs that only IT solutions for manufacturing can handle. The most common applications are:
- Artificial Intelligence (AI)Cloud Computing
- Data and Analytics
- Industrial Internet of Things (IIoT)
a) Artificial intelligence
Artificial intelligence, as a part of machine language, can be used to optimize production and transactions. This is what smart manufacturing entails. All the manual systems are overhauled and replaced with an AI system. AI collects data from all networked components in a connected factory. The data is used to reprogram workflows and optimize machinery. AI also uses the collected information to determine the optimum parameters that can be adopted to maximize revenue.
b) Cloud computing
Data collected and information produced is so enormous that it may cost a company considerable money on setting up and continually upgrading local storage. Manufacturers who find this cost unnecessary can opt for cloud computing. With cloud data storage and access, all points in a connected factory can access any required information as fast as it would be retrieved from local storage.
Since cloud storage is not in the factory, it allows remote access and monitoring of factory resources. This process is called cloud manufacturing.
c) Data and analytics
For cloud computing and AI to fully monitor manufacturing processes, a lot of data is collected, and more information generated. This data would take a lot of time to analyze and make valuable conclusions. The IT solution for this manufacturing challenge is the big data analytics that processes data swiftly. Such systems can be connected to the AI to facilitate faster decision-making and prompt response. In the end, the manufacturer saves a lot of money that could have otherwise been used to pay for data storage and analysis.
d) Industrial Internet of Things (IIoT)
IIoT connects data, people, and machines in the manufacturing industries. Such connections are not limited to time or distance. The connection of people and machines to the internet allows real-time data availability. IIoT is very reliable, and since every component can be connected to the internet, the best production efficiency can be achieved by optimizing efficiencies throughout the manufacturing operation.
As online presence keeps on growing, so do online insecurities surge. More and more devices are being connected to the internet, some of which are pathways to attackers. The IIoT, remote access, and stored data on the cloud are prime targets for hackers. These vulnerabilities need to be sealed by employing good cybersecurity IT tools. Cybersecurity focusses on detecting hacking attacks or data breaches, protecting against such, and responding to attacks already made.
Presently, IT is offering solutions to manufacturing, some of which would have been regarded as impossible in the previous century. To allow successful implementation of smart manufacturing, computer simulations are made in view of representing the dynamics of a business system. The represented model can be tested against such things as uncertain problems.
Other things, such as the speeds of various drives, the rate of discharge, and the estimated time to complete, can be incredibly simple on simulations but not mathematically. This is another area that IT solutions come in handy for manufacturing industries.
Digital Transformation and IoT in the Manufacturing industry
Digital transformation is like a constant gradual evolution in manufacturing industries. It is a process of transforming from traditional labor-intensive manufacturing methods to the modern automated systems that save on time, labor, and achieve results otherwise impossible. The IoT is among the most critical forms of digital transformation apart from automation.
Internet of Things (IoT) in the manufacturing industry
On its own, the internet of things could not see such a widespread adoption were it not for the special industrial benefits associated with it. Most of these benefits are long-term but others are immediate.
Four major areas in manufacturing have seen successful application and adoption of the technology:
1. Monitoring machinery usage
According to an ITIF study, productivity can be increased by between 10% and 25% if IoT applications are used. Monitoring machine resource utilization by IoT can boost the global economy, up by $1.8 trillion, says the study.
IoT monitors by collecting data from every connected device and/or sensor. This data is transmitted to the cloud storage for processing and analysis. After the key performance indicators have been identified, they are relayed back to the factory system via the web or mobile-based platforms. Workers can interpret and adjust production proportionately.
2. Product quality control
There are two basic ways in which the quality of production can be supervised. The most common is the inspection of work in progress (WIP) throughout the production sequence. The other is by monitoring the calibration status of the machines that make the product.
Machine operational parameters such as the speed of VSDs, humidity, temperature, and others like vibration can be monitored in real-time such that any excesses are detected, and an alert is sent. In IoT, smart tech suggests corrective measures, and in some cases, the system may have permission to autocorrect.
3. Monitoring workplace safety
Safety is of critical importance not only to critical industries like gas, mining, transport, and oil, but also any other place with persons stationed along production lines. The most common IT solution for manufacturing in such industries is the use of RFID tags and wearable tags. An RFID tag relays the location of a worker while wearable sensors collect data on pulse rate, temperature, and galvanic skin response of a worker. The data is transmitted to the cloud computing center and compared against dependent parameters such as environmental weather conditions and existent work plan systems, among others.
If an unusual heart rate is detected in a worker, for example, it is immediately relayed to them and to the manufacturing supervisors who can relieve the worker. This helps avert a would be overexertion and any resultant consequences.
4. Industrial onsite assets management and allocation
IoT offers smart management of resources in a manufacturing setup, along with other applications. The asset-related things that can be optimized through IoT include; proper asset allocation, prolonged machine service life, reliability, and revenue on capital.
IoT manages industrial assets in three areas, namely; industrial asset tracking, inventory management, and predictive maintenance.
To use IoT for asset tracking, the asset to be tracked is tagged with an RFID card that has information on the location of the equipment. If the equipment, say a mobile batching unit, is deployed, a sensor at the yard entrance scans the serial number of the equipment. The serial number could be linked with the operator assigned to the machine.
IoT is applied in inventory management to automate tracking and coverage. This ensures real-time status and location of equipment or a connected item is known; thus, the short acquisition time can be achieved, through AI.
Predictive maintenance helps a manufacturing industrial setup to avert costs on corrective maintenance. The use of IoT is expected to reduce the overall maintenance cost by up to 40%, according to Deloitte. IoT monitors the status and calibrations of inline equipment and parts. Information on the various parameters is cloud processed based on the equipment model, set mode, and other relevant parameters. More data from the ERP is compared against the input and relayed back to the onsite workers or operators.
Factors facilitating the adoption of IoT
Optimized manufacturing costs mean maximum revenue can be generated at the lowest possible cost. Things that contribute to reduced costs are;
- Reduced machine downtime due to timely predictive and preventative maintenance
- Efficiency in energy utilization
- Fewer operational staff requirement
Shortened time-time-to market
Smart manufacturing through IoT means the shortest production times can be achieved. If IoT is properly configured with AI, mind-blowing results are achievable. An example is the adoption of IoT by Harley-Davidson to reduce manufacturing time considerably from 21 days to 6 hours. This was done in the company’s New York factory.
Production of a new product begins with a single variant. As the trade diversifies, more variants, i.e., SKUs are necessary. With IoT, manufacturing operations and batch sizes can be monitored and data stored within no time. Previously, the process used to be tedious and impossible in some cases.
Need for synchronized monitoring
A manufacturing industry that has automated processes requires less staff to man the plant. To be able to monitor the various processes that depend on each other, IoT becomes a necessity. IoT facilitates corrective actions to be done not only at one point, but also on other areas that may have been affected by that one breakdown or change.
IoT adoption has, however, not been without challenges. Some of these problems encountered by manufacturing firms include:
- Shortage of qualified operators
- Huge capital investment
- Increasing cases of cybersecurity, &
- Difficulty in integrating existing manufacturing systems with IoT
IT solutions for manufacturing have played a pivotal role in the transformation of industry 4.0. Overall, the IoT application has reduced the costs of operation and maximized resource allocation and utilization. On the other hand, automation has reduced production timelines and improved accuracy in manufacture. Adopting IT solutions for manufacturing challenges may be a daunting task if done from scratch. The cost is also high, but since the future of modernization in manufacturing depends on these solutions, the earlier a manufacturer embraces the technology, the sooner the initial costs break even.