How to work with the intelligent factory

The intelligent factory works with production teams, through powerful software tools, to raise productivity by improving production plans, minimising stoppages, and accelerating troubleshooting

Intelligent factory has become a manufacturing industry buzzword, easily interpreted as a facility that has a mind of its own with minimal need for human involvement. The term is better understood as a factory that works with production teams and actively contributes towards meeting production targets and minimising waste.

Waste comes in many forms that impair overall efficiency. The smart factory combats these, including helping with time-consuming tasks to ensure faster turnaround for customer orders and assisting with machine programming and setup to accelerate new product introduction (NPI) and ensure optimum utilisation. The intelligent factory also cooperates to anticipate problems such as equipment errors or depleted component feeders and thus ensure continuous, efficient production and the highest possible end-of-line yield.

Seen in this way, the intelligent factory defines a production facility endowed with advanced tools that provide intuitive support for planners and production teams to ensure every shift can attain optimal productivity. Of course, much of the added value in the smart factory is associated with software-based tools that assist with planning and optimisation as well as managing processes and responding in real-time to issues that arise during production.

Data creation

The incoming generation of smart factory tools help accelerate laborious and time-consuming processes such as component data creation. One example is Yamaha’s YSUP-PG visual data editor, which assists by displaying component data and graphical images at the same time to simplify processes like creating and editing component identities. This saves programmers having to switch back and forth between different screens, memorising the information each time, which is a familiar pain point.

In addition, desktop trial mounting helps ensure components are setup to be correctly oriented relative to the land design long before boards start being built. Leveraging advanced 3D rendering on high-performance graphics processors can visualise how the completed assembly will look in greater than ever before (Figure 1). It can highlight any issues that may need to be addressed, in a way that earlier programming environments simply would not be able to achieve. In the past, inaccuracies in component data may have gone undetected until the first boards reached inspection or test. In addition, production equipment such as component mounters can support data creation by helping automatically generate component pickup data.

Figure 1. 3D graphics can show details such as relative heights of adjacent parts, which helps identify any problems with the data.

Optimised production planning

Smart factory tools provide enhanced capabilities for optimising production efficiency and equipment utilisation. Planners have long sought to consolidate the production of assemblies that can use the same solder type and reflow profile, to save changes to printer and oven settings. Waiting for reflow zone temperatures to stabilise in between product changeovers can be particularly time consuming, causing extended line stops.

Identifying products that can be built together to enhance efficiency and minimise the time spent setting up and changing over products is difficult to achieve, requiring human planners to consider many parameters simultaneously. The YSUP-PG Line Optimizer tool applies an algorithm that minimises production loss due to setup work and can adapt depending on the different capabilities of the various equipment models in the line. Moreover, the YSUP-PG Production Planner has a grouping function that can assign products in groups according to common components and equipment settings, also taking into account their production schedules and shipping plans. The operator can direct the grouping process and select priorities, relying on the tool to do the number crunching. Compared to manual grouping, automation improves critical indicators such as the number of group changeovers needed, and numbers of carts and feeders needed, by 25%. On the other hand, automation has saved more than 80% of work time committed to data preparation.

Another factor that can be improved with automation is material time limit management. Materials that have a finite lifetime on the production line, such as solder paste and moisture-sensitive components, can easily exceed their maximum exposure if the expiry time is tracked manually. Smart factory tools hand responsibility to machines in the line, to identify and reject expired parts to ensure all assemblies are built according to the specified standards.

Production analytics

While production is running, the smart factory provides real-time assistance by actively monitoring progress and ensuring materials are retrieved from inventory and directed to the right places at the right times. It ensures production can run continuously without stoppages and informs operators of issues that need attention.

Leveraging cutting-edge data analytics provides the foundation for tools that take the guesswork out of defect analysis. Using the YSUP suite again as an example, this tool has recently updated the main Dashboard user interface by introducing component pickup analysis (Figure 2) that automatically identifies the causes of any defects detected. It tracks errors by head, feeder, and nozzle, and then checks the status of other parts assigned to the same feeder and nozzle to determine whether the problem is caused by the equipment or the component. The tool can do this in near real-time, which saves production supervisors puzzling over how to fix problems, relieves the overheads of trial-and-error troubleshooting, and helps quickly restore maximum productivity. Ultimately, this enables every working shift to deliver consistently high production throughput and end-of-line yield, and significantly reduces stoppage time.

Figure 2. The analytics dashboard helps quickly solve the causes of pickup errors.

The Dashboard’s pickup error analytics goes further than simply highlighting causes and cures, however, by also identifying frequently occurring errors and calculating the costs of component losses to help prioritise remedial action. Maintenance teams also benefit from rich information about feeder and nozzle issues, pickup performance, and trends, to help pinpoint the causes of errors remotely and predict optimum times for repair or recalibration.

Made smarter with connectivity

There would be no smart factory without coordination between the manufacturing activities and the enterprise software directing business operations at a high level. Collecting data from factory equipment enables analytical applications in the IT domain to enhance business planning and direct continuous improvement. Modern APIs like JSON and REST enable the IT and operational domains to communicate and share data. Yamaha’s YSUP-LINK connectivity package for smart factories supports these APIs and is also fully certified according to the IPC-CFX open standard for machine-to-business and business-to-machine communications.

Conclusion

The principles driving the transition to intelligent factories aim to automate conventionally laborious and complicated tasks. Powerful software tools that utilise the latest data analytics techniques, are key enablers of the change, which can boost productivity by cutting new-product introduction time, enhancing manufacturing efficiency and equipment utilisation, and helping to avoid or minimise the impact of any errors. Now the smart factory has arrived, the scene is set for future generations of software tools to further accelerate progress.