In questi giorni mi sono chiesto una cosa: Come mai le stesse tecnologie usate in CINA non vengono applicate anche da noi ?
Robot disinfettanti, caschi intelligenti, droni dotati di telecamera termica e software di riconoscimento facciale avanzato sono tutti impiegati nella lotta contro Covid-19 nel cuore dell’epidemia in Cina.
La tecnologia sanitaria viene utilizzata anche per identificare i sintomi del coronavirus, trovare nuovi trattamenti e monitorare la diffusione della malattia.
Robot in soccorso
Diverse aziende cinesi hanno sviluppato tecnologie automatizzate per la somministrazione senza contatto, la disinfezione a spruzzo e l’esecuzione di funzioni diagnostiche di base, al fine di ridurre al minimo il rischio di infezioni incrociate: robot, droni per la conduzione di immagini termiche e per il trasporto di campioni mediti
Big data per controllare la pandemia
Oltre ai robot e ai droni, la Cina ha anche mobilitato il suo sofisticato sistema di sorveglianza per tenere sotto controllo gli individui infetti e far rispettare le quarantene.
Le telecamere di riconoscimento facciale sono comuni in tutta la Cina e ora le aziende stanno aggiornando la loro tecnologia per scansionare le folle alla ricerca di febbre e identificare gli individui che non indossano maschere.
By analyzing vast amounts of data collected from a network of connected sensors installed in production systems, it enables companies to make reliable predictions of how the condition of a machine or system will develop over time and when maintenance is required. However, the conditions of the production systems have a direct influence on the quality of the final product.
Therefore, it is possible to establish a very close link between predictive maintenance and predictive quality. Finally, these new technological scenarios offer opportunities for the development of service models, allowing machine manufacturers to set new standards for managing customer relationships.
Model and infrastructure
The predictive model is at the heart of all predictive maintenance scenarios: the modeling starts with the identification of relevant parameters, such as temperature, pressure, vibration or visual characteristics. The basis is in the historical data. By applying the model to the historical data, the model can be tested to identify its capabilities and the forecast accuracy can be adjusted. Machine Learning technology can support this process, making the model more and more “smart” and increasing its predictive power.
As a prerequisite, the IT infrastructure and networks must be able to handle high volumes of data. Internet of Things and Big Data are the main keywords in this regard. The harmonization of different types of data is of crucial importance to discover hidden correlations between measured values and the propensity to defect. In this context, cloud technology offers some central advantages such as high scalability and global accessibility via the Internet.
The value of JOULEHUB EXPERIENCE
With JOULEHUB EXPERIENCE, JOULEHUB offers a production operations management platform that integrates all shopfloor equipment making data accessible to a wide range of applications. Through JOULEHUB EXPERIENCE, condition monitoring data from the equipment can be easily analyzed for predictive maintenance purposes.
JOULEHUB also supports industrial companies through tailor-made innovation and service design, developing new business models based on the latest technologies and management consulting, to successfully transform companies in line with the paradigms of Industries 4.0.
JOULEHUB can leverage extensive knowledge and experience in all relevant areas, such as Machine Learning, Cloud Computing, Data Science and IoT and Architecture.
Predictive maintenance in practice
The higher the quality requirements for a product, the less tolerable the deviations in production parameters become. A metallurgical production site producing high-precision components for the automotive, pharmaceutical, chemical or medical industries can predict material defects with high accuracy by closely monitoring production conditions and the status of production facilities.
These analyses allow rapid adjustments to ongoing production processes and to suspend subsequent production steps to save energy if necessary. On the other hand, the correlations between machine performance and defect susceptibility become visible. Maintenance can be scheduled accordingly to ensure adherence to previously defined thresholds. This proactive maintenance avoids unplanned and costly downtime and contributes to predictive quality assurance.
The main advantage for the manufacturing industry is superior overall equipment efficiency (OEE):
- Increased availability due to more efficient maintenance planning;
- Improved product quality through faster identification and removal of quality deviations;
- Reduce warranty cases and rejects through improved product quality.
- Possibility to detect, visualize and modify in real time the production parameters;
- Possibility of optimizing production according to different criteria;
- Efficiency of energy consumption;
- Automatic control of the use of PPE;
- automatic movement of goods and their tracking in the company;
- efficiency of the processes of management of incoming goods;
- automated management and warehouses;
- possibility to reorder in an automated way the goods in exhaustion;
- possibility to have transactions conditioned to the state of the goods;
- automatic certification of transactions;
- transition from preventive to predictive maintenance;
- Increasing operator safety;
- reduction in operator training times and costs;
- reduction of machine downtime;
- automation of the loading/unloading of the warehouse in the management system;
- automation of unloading scheduling;
- increase of the transporter/internal warehouse coordination;
- modelling of the behaviours of the different actors along the supply chain;
Distribution and sale
- acquisition of purchase or interaction data directly from the store shelf;
- acquisition of real and real time sales data;
- automation of invoicing.
There’s no question that the manufacturing industry is moving at a rapid pace. Assembly lines are becoming smarter, R&D becoming more innovative, and operations becoming slicker. Manufacturing businesses are embracing new technologies and utilising everything from the Internet of Things, to smart devices, in order to build a competitive advantage and stay ahead during highly competitive times.
But while new technologies are coming thick and fast, there is one application that has been a vital tool in the manufacturer’s arsenal for the last 50 years. There’s one application that streamlines efficiencies across entire supply chains and there’s one application that is continuing to grow in order to keep up with, and seamlessly integrate with new, more recent technologies. That technology is the humble Enterprise Resource Planning (ERP) system – a technology that has been around for decades, but which remains the next big thing in Industry 4.0.
Boosting factory efficiency
The smart factory of the future is one that is capable of delivering shorter product runs, manufacturing more complex products with more frequent material changes, resulting in quicker deliveries, different mixes of packaging and distribution, better change forecasting, supply chain management, and product traceability.
ERP has been helping businesses achieve all of this for many years. Yes, the stories of manufacturers saving time and money with ERP are everywhere – and they’re all true, but many of these document a single business process. Imagine the efficiencies that a business could achieve with seamless integration of planning, materials management and procurement, manufacturing, financial and business intelligence processes through one single system. ERP can deliver complete factory automation and unify multiple business processes, and disparate systems to better connect all facets of your supply chain. It can enable you to work smarter, faster, and spend more time focusing on product innovation and servitization, instead of operating manual tasks to try and plug the gaps left in your poorly automated supply chain processes.
Get a handle on those robots
Like it or not, the age of robotation is coming to manufacturing. Industry 4.0 is a period where manufacturing businesses are improving machine uptime, decreasing labour costs, consolidating factory space and saving on capital expenditure – robots facilitate all of these.
However, the introduction of robots to the factory floor means that a busy manufacturing manager now has yet another asset to manage. And what happens when one of them ultimately fails in a way that a human worker rarely does?
By linking robots to your ERP system, and integrating their data streams into your ERP data, you can better schedule robot maintenance and analyse their output to make them move orders forward more effectively. And by using ERP to adjust your product designs and held inventory, you can consistently change and modify your designs and materials to reap even more value from your robots.
Help your business leverage the Internet of Things
From product development to production control and after-sales, connected devices are providing manufacturing businesses with a higher level view of their supply chains and enabling them to make better informed decisions, more quickly. Add the Internet of Things into the mix, and the possibilities for a manufacturing business become endless.
Many manufacturing businesses are starting to fit sensors to their products to analyse their performance in terms of their effectiveness safety levels, durability and other critical values. By sending this information directly to your ERP solution, you can update Bills of Materials, adjust design specifications and adjust processes to continually improve your products through production. By leaving sensors on products post production, you can feed this information into ERP to track the lifecycle of a product and use this information to deliver a greater service to your customers by alerting them when a product may need maintenance, and to streamline or alter your production strategy for continuous product improvement. The use of sensors in manufacturing post production is nothing new, but ERP offers a way to route the masses of data collected by the sensors into your design and engineering processes to enable continuous improvement.
Greater productivity, improved efficiency and higher flexibility are the three traits of any competitive manufacturing business during Industry 4.0 and unsurprisingly, three benefits that ERP can deliver. The businesses that truly thrive during the fourth industrial revolution will be those that continue to use ERP as a mission critical supply chain tool, and continue to think up new and innovative purposes for their solution. After all, ERP has evolved throughout the last 50 years, just imagine where it will be in the next 50?
Digitization, automation, and data collection has been driving the fourth industrial revolution in recent years, otherwise known as Industry 4.0. We’ve seen a phenomenal rise in the establishment of smart factories and smart data, but how has Industry 4.0 impacted the supply chain? The supply chain network is a complex and multi-faceted web. It is all too easy for one weak link to completely break down the chain. By digitizing the vital processes that make up the supply chain, manufacturers will not only future proof their business but will benefit from a significant rise in productivity and efficiency.¨
Building one transparent ecosystem
For any manufacturer, regardless of the size of the company, the supply chain is a hugely complicated and multifaceted eco-system. A lack of clarity can mean that processes and relationships can break down, disrupting the efficiency of the entire chain. Complete transparency enables businesses to not only respond to problems in real time but also to anticipate any issues and respond to them in advance.
Ultimately, digitization is the key to creating a transparent supply chain ecosystem. Through the installation of a digitized and fully integrated supply chain network, companies are able to respond to customer demands more effectively and efficiently, ultimately improving productivity.
Investing for the future
There is no quick fix to digitising an entire supply chain. This complete transition will take time and will be costly, but once completed manufacturers will reap the benefits for many years to come. In the last ten years, Essentra Components has invested in over £13.5 million in upgrading, future proofing and digitising the manufacturing operations at their Kidlington site in the UK.
The creation of smart machines, linked to each other and to the cloud, ultimately speeds up set up times and installation processes, driving efficiencies in production whilst also reducing costs. By linking these smart machines to the cloud, process engineers are able to access machines remotely, diagnosing and resolving problems more quickly, ensuring the machines are back up and running in the shortest time possible. This quick exchange of information is revolutionary and boosts the agility and responsivity of the entire chain.
There is no quick fix to investing in the digitization of the supply chain network but, manufacturers wanting to compete on a global scale must begin implementing a digitized supply chain network now. By doing so, businesses can respond to customer demand in real time, ultimately improving the experience for both the manufacturers and the customers. Manufacturers must be reassured by the fact that this long term investment will pay dividends to the company for many years to come.
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Based on the adoption of interconnected and intelligent technologies and solutions, the new paradigm of Industry 4.0 design is gradually changing production processes within Italian manufacturing companies.
However, the digital innovations of the Fourth Industrial Revolution not only affect the way factories produce, but also invest in the design and engineering techniques of the industrial product.
The 4.0 technologies allow a significant improvement in product design thanks to the integration of software components (sensors, GPS) that, connected to machinery or other physical objects, make it possible to collect data from the field. Making products intelligent through the Internet of Things has many advantages at every stage of the product life cycle, including design.
Access to data and information during the use of an industrial product enables designers to constantly monitor its performance and the way it is used. Thanks to real-time monitoring, for example, it is possible to effectively redesign the infrastructure of the digitized product in order to achieve high levels of energy savings, avoid downtime and consequently optimize production flows.
In the automotive sector, more and more companies are relying on IoT to automate various safety procedures for their vehicles. For example, the design of cars with vehicle proximity control sensors, stop-and-go assistance, emergency brakes or 3D maps enables the collection of information that can be used upstream by designers to improve the consumer driving experience and make it safer.
Once this scenario is outlined, it is quite clear to manufacturing companies that they need to rely on technologies based on data collection to improve not only the production of industrial goods, but also their design. In order for the potential benefits of Smart Manufacturing to become effective, the adoption of 4.0 technologies must therefore be accompanied by the implementation of management systems that make it possible to store, share and use data collected in the field and ensure proper management of information throughout the product lifecycle.
How do you evaluate the design activity in your company?
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