A smart factory is defined as a factory in which physical production processes and processes are combined with digital technology, smart computing and big data to create an opportunistic system for companies focusing on production and supply chain management.
The smart factory is aspect of Industry 4.0, a new phase of the industrial revolution that focuses on real-time data, embedded sensors, connectivity, automation and machine learning.
As factories evolve in light of the data revolution, companies need to rethink how they deal with everything from automation strategies to workforce development tactics. Along the way, manufacturers will need modernized tools, including robust, flexible enterprise resource planning systems as a data and transaction backbone, to help them adapt quickly as they move toward the future of the smart factory.
A smart factory is easiest to imagine compared to a more traditional yet modernized manufacturing environment. As manufacturers have embraced automation in today’s climate, many have automated systems in various parts of their business. They may have tools to automate supply chain elements, such as online production machines, barcode scanners, assistive drones, or similar tools.
At the same time, the production line can be automated so that the product goes through different stages of production without human intervention using robotics. Testing and quality control could include cameras and sensors that automate most of the work there as well. In many factories, each of these automated processes is interconnected, requiring frequent human interventions to make transitions between different phases of operations.
Moreover, the lack of connectivity between machines and different business areas means that human workers are constantly analyzing different sets of data and reports to identify problems and potential areas for increased efficiency. The factory of the future is one in which these various systems are no longer isolated. Workflows and data processing will be optimized for various activities, from warehousing to sales area and sales office.
The smart factory brings the fourth industrial revolution that drives more intelligent production. Some of the ways this can be played out include:
These are just three examples of how a smart factory is shaped. The movement boils down to a simple idea: instead of isolated automation with frequent human interventions, a smart factory removes barriers between all phases of operations to automate data analysis and operational workflows more deeply in a single connected ecosystem.
Each factory that can be called a “smart factory” includes 5 key features:
These four levels of data structure can help you assess where you are progressing in achieving a smart factory and what steps you need to take to advance to the next level.
First level: available dataThis is probably the current status of most factories. The data is available but cannot be easily accessed. Sorting and analyzing data requires manual labor and can be time consuming, creating more inefficiencies in the production improvement process than anticipated or required.Second level: accessible dataAt this stage, the data is displayed in a more digestible form. The data is structurally organized and properly sorted in one place with additional systems that help visualize the data and display it on the dashboard. The factory is able to conduct proactive analysis, although this could still require a little time and effort.Third level: active dataActive data means data that can conduct proactive analysis using machine learning and artificial intelligence to create insights without much human supervision. The system can identify key problems and anomalies in order to predict failures with great accuracy and inform relevant people with valuable insights at the right time.Level 4: Action-oriented dataAt this stage, machine learning can generate effective solutions to problems identified in earlier stages. Manufacturing machines and devices associated with this module or system can make these changes without human intervention. Data collection, problem identification, and solution generation occur in sequence with little or no human input.
First level: available data
This is probably the current status of most factories. The data is available but cannot be easily accessed. Sorting and analyzing data requires manual labor and can be time consuming, creating more inefficiencies in the production improvement process than anticipated or required.
Second level: accessible data
At this stage, the data is displayed in a more digestible form. The data is structurally organized and properly sorted in one place with additional systems that help visualize the data and display it on the dashboard. The factory is able to conduct proactive analysis, although this could still require a little time and effort.
Third level: active data
Active data means data that can conduct proactive analysis using machine learning and artificial intelligence to create insights without much human supervision. The system can identify key problems and anomalies in order to predict failures with great accuracy and inform relevant people with valuable insights at the right time.
Level 4: Action-oriented data
At this stage, machine learning can generate effective solutions to problems identified in earlier stages. Manufacturing machines and devices associated with this module or system can make these changes without human intervention. Data collection, problem identification, and solution generation occur in sequence with little or no human input.
With the advent of Industry 4.0, the idea of a smart factory is regularly highlighted. However, there is no single approach to creating a smart factory.Realizing that there is no single path, and that the development of a smart factory is an ongoing evolutionary process actually makes it much easier to start a journey.
This could involve launching one production line or even one asset and maximizing its performance. This means automating, for example, batch controls or improving the way you generate, collect, centrally store, present, analyze, and then use data to make real decisions.
This small start-up is easy to manage, less risky and cost-effective, while allowing you to test and prove concepts. You will also see how the benefits of Industry 4.0 will affect your business and facilities and what challenges lie ahead.
There are numerous benefits of a smart factory that are already listed and clear for themselves, and most factory owners emphasize the importance of connecting assets, resources, and data from different platforms and systems in one place.
Some of the most important values and capabilities of smart factories are:
“Illuminating” hidden data: Connected smart factories provide data that managers have often never had access to before, illuminating things and information that have always been present, but in the “dark” due to a lack of digitization.
Improving existing systems for new value: Companies can develop and improve existing methodologies and disciplines, such as lean manufacturing and talent management, to discover new ways to create value, boost productivity, and make faster decisions.
Use AI to move to the next level: When everything is connected, business is full of data. Businesses need tools to somehow understand all this information in a way that people cannot and do not manage values quickly, proactively and flexibly.
Smart factories optimize efficiency and productivity by expanding the capabilities of both production machines and people. By focusing on creating an agile, iterative manufacturing process through data collection, smart factories can use stronger evidence to help decision-making processes.
By constantly improving the productivity of manufacturing processes, smart factories can reduce costs, reduce downtime, and minimize waste. Identifying and reducing lost or underutilized production capacity means opportunities for growth without investing in additional financial and / or physical resources.
Manufacturers can implement a smart factory in many different ways - both inside and outside the four factory walls - and reconfigure it to adapt when existing priorities change or new ones emerge.In fact, one of the most important features of a smart factory "agility" also offers manufacturers more opportunities to use digital and physical technologies, depending on their specific needs.
The specific impacts of a smart factory on production processes are likely to be different for each organization. Deloitte has identified a set of advanced technologies that typically facilitate the flow of information and movement between the physical and digital worlds.
These technologies drive the digital supply network and, smartly, the factory, creating new opportunities for the digitization of production processes:
Production processes - Additive production enables rapid production of prototypes or spare parts. Advanced planning and scheduling, with the help of actual production and inventory data, reduces waste and reduces cycle time. Robots and cobots perform routine tasks with high precision and minimal cost.Warehouse - Autonomous robots perform simple storage tasks.Inventory monitoring - Sensors monitor the real-time movement and location of raw materials and finished products, and automatic analytics enable inventory optimizationQuality - Real-time monitoring of equipment and anticipation of possible quality difficulties.Maintenance - Predictive maintenance simplifies processes and prevents sudden failures.Environment, health and safety - Sensors monitor operation and prescribed distances, conditions, movements and more, thus preventing threat potentials.
Production processes - Additive production enables rapid production of prototypes or spare parts. Advanced planning and scheduling, with the help of actual production and inventory data, reduces waste and reduces cycle time. Robots and cobots perform routine tasks with high precision and minimal cost.
Warehouse - Autonomous robots perform simple storage tasks.
Inventory monitoring - Sensors monitor the real-time movement and location of raw materials and finished products, and automatic analytics enable inventory optimization
Quality - Real-time monitoring of equipment and anticipation of possible quality difficulties.
Maintenance - Predictive maintenance simplifies processes and prevents sudden failures.
Environment, health and safety - Sensors monitor operation and prescribed distances, conditions, movements and more, thus preventing threat potentials.
Companies are increasingly transforming to embrace the smart factory movement. It’s hard to say when an intelligent manufacturing environment will be the new normal in the future, but companies are already working on that future.
A few key things will completely change the factories we know today and make the transition to smart factories easier:
The Industrial Internet of Things (IIoT) goes beyond proof of concept and expands adoption and application in all industries. A survey by Microsoft’s giant IIoT found that 94% of companies said they would implement IIoT strategies by the end of 2021.
Applications of artificial intelligence and machine learning are becoming even more important tools for data analytics. These two technologies are responsible for taking production to the next level. They provide three core values, which according to experts are speed, scale and practicality.
Speed and scale speak to the advantage of automating the analysis of massive data sets, as opposed to assigning tasks to human analysts. Thanks to AI and machine learning, it is now possible to analyze complex data sets in a fraction of the time.It’s not just because computers have become faster or better. This is because AI and machine learning algorithms have become extremely good at data analysis. And, because it’s easy to customize that analysis in the Cloud.
In terms of convenience, the addition of AI and machine learning analytical tools has made them intuitive, easy to use and much more reliable.
5G will allow manufacturers to improve latency and enable real-time communication at a scale not seen before.
With 5G, manufacturers can begin to improve the use of sensors, Clouds, quality checks, centralized monitoring, etc. However, not every manufacturer will be able to take advantage of 5G (depending on the area). But those who will, will have a great opportunity to improve their processes and continue to be more efficient.
Cloud Computing enables smart factories to store, process and share data with more flexibility at a lower cost than traditional local capabilities.Interconnected devices and machines at the point of sale benefit from the rapid transfer of large amounts of distillable data to provide feedback and make real-time decisions.
There are SaaS solutions on the market specifically developed for the industry. MachineDesk enables digitization and easier transition to smart factories. By monitoring, managing and controlling all the production and business processes from one place, it automates business and emphasizes the benefits of Industry 4.0.
As digital production continues to evolve in the coming years, manufacturers must keep pace with change. For some, this can be a challenge; however, it is important for survival in an increasingly competitive global market.
Smart factories are the solution for manufacturers who want to harness the potential of their resources, staff skills and time to achieve competitive advantage. It is true that launching the Smart Factory and Industry 4.0 concepts requires significant investment, effort and strategy. But in the long run, given all the benefits that a fully automated and intelligent factory can have, the effect of a well-implemented smart factory solution should bring a return on such a significant investment.
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