The accrued benefits from automating every traditional process in today’s manufacturing facilities are the driving force behind Industrie 4.0. Robust industrial cloud solutions have an essential role to play in the implementation of this change since industrial clouds are figuratively the foundation that supports the interconnected shop floors or the smart factories of today and the future. In this post, we will cover the different ways an industrial cloud can be used to implement Industrie 4.0’s fundamental principles.
This article covers:
How an industrial cloud solves the problem of interconnectivity across shop floors
How an industrial cloud helps with predictive maintenance in Industrie 4.0
The role an industrial cloud plays in implementing Industrie 4.0 in lean manufacturing
Tracking the activities of automated material handling equipment in Industrie 4.0
How an industrial cloud streamlines discrete manufacturing tasks
Connecting the Dots across Industrial Manufacturing Facilities
The guiding principle of every Industrie 4.0 compliant business plan is automating the production cycle and leads to Industrie 4.0 factories being smart factories. Extensive planning is required, which will include equipping manufacturing devices and material handling equipment with intelligent features. Once achieved, the data produced must be collated and analyzed to manage production life-cycles digitally. This is where the scalable, network integration features of industrial cloud solutions are critical.
Industrial cloud solutions create the perfect ecosystem for storing customer data, smart machine data, inventory, and supply details. With this information, you can then proceed to automate the production cycle at will. An example is the manufacturing of tooling devices using a smart CNC machine. An intelligent CNC machine is one equipped with precision sensors that produce data. An industrial cloud solution such as the Corvina Cloud 2.0, can create an interconnected network or ecosystem consisting of data. This ecosystem will manage the data from the machine sensors, ERP or CRM databases, and inventory tickets. In this ecosystem, relationships across every device and application used in a shop floor can be managed in real-time.
The benefits of an interconnected shop floor range from increased productivity to meeting demand: Alibaba’s interconnected automated guided vehicle (AGV) can serve as a case study. Here, an industrial cloud solution analyzes the distance between workstations, materials demanded, and delivery speed. The information needed to determine the speed and route of an AVG is then set, stored, and transmitted by an industrial cloud solution to the AVG.
Enabling Predictive Maintenance in Distributed Intelligence Systems
The use of machines and systems with distributed intelligence is another crucial aspect of making a move to Industrie 4.0. Field-level components and systems integrated with distributed intelligence can take automation to the next level. These components can perform set tasks independent of human assistance using only the instructions received from a higher-level system. An example of such a task is a machine running its diagnostics and executing predictive maintenance activities when required.
It is imperative to note that a system with distributive intelligence is generally equipped with many sensors and applications that enable automation. This includes motion sensors, vibration sensors, and integrated software applications which all produce data. The data they provide need a higher-level system where they can be stored and analyzed. An example of such a higher level-system is Corvina Cloud 2.0. This cloud-based solution can serve as the higher-level system. It collects the data produced by the interconnected sensors and software in a distributed intelligence system.
Corvina Cloud can then be used in conjunction with the software in the distributed intelligence machine to produce instruction tickets that gets the system to act. This action could be the running of occasional diagnostics on the moving parts of a manufacturing machine. The data collected from multiple distributed intelligence components can also be applied to new but similar devices. These new components or systems can be provisioned with the information needed to execute their preventive maintenance tasks before faults occur. The advantages of real-time predictive and preventive maintenance include; increasing the lifespan of manufacturing systems and reducing overhead costs. You can also learn more about predictive maintenance here.
Integrating Lean Six Sigma Processes Using Industrial Cloud
One of the much-touted benefits of integrating Industrie 4.0 in your business is its support of lean manufacturing principles. It is a fact that Industrie 4.0 seeks to eliminate waste while reducing operational cost. Integrating industrial cloud solutions is the most efficient way to achieve these admirable qualities while running your automated facility. This is because industrial cloud solutions can help your Industrie 4.0 compliant facility create guidelines to end waste.
Every possible variable or characteristics of a production cycle must be measured, analyzed, controlled, and in some cases, improved, to achieve stable production results regularly. Industrial cloud solutions are the perfect tools for collecting data that makes measuring and analyzing the performance of different production variables. These solutions collect variables such as; customer demand data, machine capacity data, and the number of materials needed to meet customer demand. On analyzing the data, uncertainties tied to the process of production can be minimized. Thus, material waste will be reduced while production time-lines will be adhered to.
Another aspect to consider is ensuring a product meets preset quality standards and is free of defects. Industrial cloud solutions can be used to monitor the entire production cycle and hence help to accomplish these objectives. This includes tracking the activities of third-party suppliers and comparing samples from each production stage to a preset model in real-time. The data collected during the monitoring and analytical process can then be used to assess future production cycles.
The integration of a robust industrial cloud is also useful for discrete manufacturing. In this case, distinct and non-generic items are the products to be manufactured. The ability to monitor the data automated machines produce during discrete manufacturing ensures each workstation is provided with the right materials and tools required in executing specific tasks. An industrial cloud solution can also give instructions on the material handling equipment to be used for different tasks and accurately tag routes to the receiving workstation. So, industrial cloud solutions can eliminate material waste and speed up production during discrete manufacturing. This is why the distinct manufacturing industry is expected to spend approximately $20 billion in 2019 on industrial cloud solutions.
The move to Industrie 4.0 is one that is expected to redefine manufacturing, as we know it, in the 21st century. To develop a successful blueprint, facility managers must understand the benefits associated with integrating robust industrial cloud solutions for technologies such as data-driven plant performance, predictive maintenance, virtual training and validation, and others. These benefits include reduced operational cost, increased efficiency, and excellent returns on your industrial cloud investments. You can learn more about robust industrial cloud solutions that fit your specific business needs by contacting us today.