Currently, the utilization of connectivity with regard to management systems (ERPs) is something very common among the majority of manufacturing companies. Some already work with an MES/MOM solutions and others have the implementation of one on their roadmaps.
The main drivers that motivate companies to include this type of software in their system landscapes are:
- Production monitoring: Making the planned production process converge in the ERP with the information provided by the machines enables real-time monitoring of manufacturing order execution without having to be physically present in the factory.
- Increasing operational efficiency: By calculating the cycle times for each process, it is possible to find the bottlenecks that prevent you from achieving the take time required by the client and utilize the balance of resources to obtain it.
- Asset control: The OEE (Overall Equipment Effectiveness) is the indicator par excellence for machine monitoring. This is because what this KPI monitors enables us to qualify our asset management.
- Improving the quality of Master Data: With the increase of real-time manufacturing in the ERP, one manages to adjust both the calculation of the standard cost as well as production planning.
The Convergence of Manufacturing with the World of E-Commerce
Traditionally, repetitive manufacturing has operated based on production lots. It defines both the economic lot as well as the quantity of a same model to be produced, and where the costs for production preparation and inventory even out.
Currently, we find ourselves facing a paradigm shift in this sense. Now that connectivity with bidirectional machines has been resolved, it is time to capitalize on investments that have already been made in infrastructure and software in order to develop more innovative new use cases. It is a case of the Lot Size One concept. Basically, the objective is to reduce the lot size to its minimum expression; that is to say, One.
In this way, we are going to enable a client purchase order made directly over the web to be converted into a need that the planning system converts directly into a manufacturing order.
The production schedule is lowered in a sequenced manner directly into the machine without any need of human intervention. The machine is capable of producing only what is requested by the client without generating overstock.
From a physical standpoint, this isn’t an obstacle either. Currently, the manufacturing lines are becoming more and more automated, and automated guide vehicles (AGVs) now have a significant presence in factories. This enables the construction of manufacturing lines that are completely flexible and have the ability to carry out model changes in a way that is completely autonomous.
With the implementation of this type of use case, we not only manage to reduce the stock of products finished at the plant, we also manage to have an impact on the end client’s Purchase Experience. This is not only going to allow them to choose one of the models defined by the manufacturer, it is also going to be capable of adjusting to their preferences the product that best satisfies their needs and concerns.
Nowadays, the user experience is more and more a deciding factor in the client’s purchasing decision, but this concept not only applies to “Business to Customer” business models, it is also entirely applicable to “Business to Business” businesses. It is also closely aligned with the use of the Just In Time or Just In Sequence methodology. If you work this way with your client (especially with JIS), you are very likely financing part of their provisioning stock. By implementing this type of use case in your manufacturing line, you will be able to substantially reduce your levels of final product stock, which will have a corresponding impact on your profit and loss statement.
Collaboration between Humans and Robots
In the first place, it is easy to identify which activities can be assigned to a robot and which ones a human should perform. However, as we automate manufacturing operations, this boundary becomes thinner. It is here where, for safety reasons, collaborative robots come into play that are prepared to operate within the same work areas as humans. These come to a stop whenever they are touched.
Orchestrating this type of operations isn’t something simple; there needs to be a brain that monitors each one of the operations and indicates both to robots and humans what, when and how to carry out each operation according to plan. Responsibility for this synchronization falls to Manufacturing Execution (MES) type systems.
There is a lot of interdepartmental communication or transactional administrative activity surrounding production that is likely to be robotized. This doesn’t mean that a robot physically moves from the production line to the warehouse to ask for material. It’s much simpler than that...
Industrial PLCs or even sensors added at strategic positions on the production line continuously measure variables with information that is highly-valuable in production processes. Combined with the monitoring of these variables, it is possible to automate thousands of administrative operations that bring real-time value to the process.
If we talk about continuous production in terms of quality control, we ask ourselves why we bother to define sampling plans, sample sizes, etc… if we can monitor the majority of real-time production variables and only get rid of what is flawed?
Furthermore, we obtain traceability of the analogical parameters for manufacturing; in this way, if a lot turns out to be defective, it is possible to know under what conditions it was manufactured and to define new alerts that obligate us to carry out a quality inspection.