Intelligent manufacturing is the use of the combined intelligence of machines, software, people, and processes to improve the overall viability of manufacturing. It optimizes manufacturing resources, reduces wastage, and enhances business safety and value while fulfilling the needs of customers and manufacturers.
With advances in the manufacturing technology and increasing market competition, advanced manufacturing technology is the number one priority for economic growth in most countries. Germany introduced the industry 4.0 concept in 2013, while in 2014, the US government announced the National Network for Manufacturing Innovation.
Modern manufacturing systems are complex, especially after integrating all elements or units into a standard system. Process related decisions have become more complicated. There is a need to fully utilize loads of manufacturing data and the ability of computing intelligence to improve the manufacturing decision-making process.
Intelligent Manufacturing Enablers
Analytics is the process of deriving knowledge and information from big data by discovering hidden correlations and clusters and uncovering systematic patterns to make better manufacturing decisions. The manufacturing process features numerous data, from machines, logistics, production, and customer feedback.
New schemes and procedures have been unveiled in big data analytics such as cognitive ML, statistical modelling, correlation, and clustering. This way, only relevant information is used; thus, the right decisions are made expertly. Due to its potential, big data analytics is becoming more vital for advanced manufacturing systems.
Machine learning is the capability of a computer to learn and understand physical systems via computing algorithms related to data. Examples of machine learning methods include artificial neuron networks, data mining, statistical pattern-recognition algorithms.
With a machine learning algorithm, a machine can quickly learn its working conditions and baseline automatically. It also becomes easier to create and advance a knowledge base through the manufacturing process.
Intelligent manufacturing technology has been improving significantly in recent years. Shortly data and information will be captured in real-time by advanced transducers and sensors from all sectors in the product life cycle. Cloud computing will then process the data, and correct decisions are made autonomously and accurately with limited or zero human intervention.
Advantages of Intelligent Manufacturing
- Improved productivity: With access to data throughout the entire manufacturing chain, the manufacturer can easily identify what he or she needs to adjust.
- Higher quality products: Improved productivity saves money that can be used to cover product development and advancement.
- Energy efficiency: Manufacturers can reduce waste and in turn, reduce carbon footprint.
- Increased manufacturing jobs: Adopting intelligent manufacturing increases technology-based jobs and attracts a tech-savvy, younger workforce.
The Need for Localization
Manufacturers around the world no doubt will adopt intelligent manufacturing to gain a competitive edge in the industry. Investing in smart new equipment, both machinery and software programs, is an excellent way to start.
However, these manufacturers will demand that the software programs, and equipment that they will purchase, and pay good money for, be localized in their workers' native language where their factory is located.
This means that whether your company sells instrumentation solutions, metrology services or machinery manufacturing automation equipment, software, or technology, you need to consider having your offering translated to add value to your pitch and stay ahead of the competition.
You might have to translate software, translate technical documentation, or even FAQ, into Chinese Simplified, Mexican Spanish or Malay, whichever it is , do consider working with a software translation service professional with proven experience of manufacturing industry translations.