Boost SMT line productivity with automated troubleshooting tools
YAMAHA SMT technical article

Boost SMT line productivity 
with automated troubleshooting tools

New analytics tools raise SMT production-line efficiency and reduce stoppage time 
 by identifying the causes of defects and recommending corrective actions

Although surface-mount assembly involves great precision and reliability, things can go wrong when operating continuously at high speed. In the event of errors and exceptions, the team in charge of production needs to restore full-speed operation as quickly as possible.

Whenever the line is stopped, the business incurs costs that detract from profitability. These costs include not only the direct cost of lost production but also labor costs while the line is stopped, the cost of overtime and rush orders to catch up after the line is restored, and the cost of any rework or items scrapped due to the problem that caused the stoppage. There are costs associate with inventory waiting and the disruption to the normal flow of operations can cause inefficiencies. Moreover, there can be impact on customer commitments that can result in financial penalties. 
On the other hand, it can be important to stop the line, if a problem is detected, to prevent production of defective units from continuing. The operator or production supervisor needs to know as quickly as possible in the event of an error. 

Boost SMT line productivity  with automated troubleshooting tools

 Line stoppages are undesirable and manufacturers need to ensure this happens as infrequently as possible to ensure best productivity and minimize unwanted costs. When stopping cannot be avoided, production needs to be restored as quickly as possible. ​

Yamaha SMT software

Use automated troubleshooting tools to boost SMT line productivity

Today’s assembly equipment is loaded with sensors to detect issues such as blocked nozzles or pick-up misalignment. Automatic inspection can be performed at multiple points in the line: e.g. SPI after screen printing or AOI after component placement, and reflow, using the results to assist troubleshooting in real time.

Manufacturers rely on software tools to help manage production equipment, detect any exceptions and defects, and provide information to production supervisors.

These include dashboard applications that provide an instant overview and judgement of equipment and production status. There are also value-added tools such as Yamaha’s QA Options and the closely related Mobile Judgement app. 
Mobile Judgement can send details of any detected defects, including inspection images, directly to the supervisor’s smartphone to help assess the severity of the problem. Based on personal judgement, the supervisor can instruct the line to stop immediately if necessary until the issue can be solved.

Yamaha YsUP analytics dashboard

What is the Human & Machine interface?

Yamaha machines and humans interact to solve the problems

It is the applications where machines and humans interact to solve the problems that inevitably arise during the normal course of a shift. The team in charge must apply their skills to deliver the required quantity of each batch and ensure that production runs to schedule. 
This approach can be dependent on the quality of the tools provided to visualize the data captured from the various locations throughout the line.

Identifying the cause of faults and applying a fix, quickly, also depends on the skills and knowledge of the supervisor staff-members present in the factory. If the company’s top supervisor is not on duty for any reason – maybe they are working another shift, on vacation, perhaps on sick leave – productivity could be impaired.

The latest advancements in data science can help to eliminate dependence on individual judgement by automatically identifying the causes of any defects or other production problems. Guiding operators directly to these causes permits more consistent production performance.   

As an example of this emerging generation of software tools, the latest Yamaha YSUP Analytics Dashboard contains advanced tools that use statistical techniques to identify most likely causes of detected defects. It also recommends suitable corrective actions. 
The analytics tools work in addition to graphical tools that help visualize the performance of equipment in the production line (figure 1).

Yamaha Dashboard visualization tools help assess process performance  
Figure 1 | Dashboard visualization tools help assess process performance. ​ 
Data sourced from:  1) Printer + SPI   |   2)  SPI + Pick & Place + AOI
pre / post reflow oven   |   3) Pick & Place + AOI pre / post reflow oven

The new YSUP Analytics Dashboard presents information in an easy-to-read format that can be interpreted at a glance. Ultimately, this enables every working shift to deliver consistently high production throughput and end-of-line yield, and drastically reduces stoppage time.

Based on a relational database with built-in querying capabilities that analyze data unaltered. The software identifies probable causes of recorded exceptions in near real-time using statistical techniques. The automatic analysis capabilities of the new dashboard application that enable any authorized user to extract the production insights they need, analyze errors, and view corrective actions at any time.

The tools available include automatic SMD pickup error analysis, which uses analytical methods including flow judgement, error-code diagnostics, health-check data diagnostics, and image-recognition diagnostics. The user can view the time and circumstances of any pickup errors, see the exact location, and view corrective actions (figure 2). 

Yamaha has verified the accuracy of automatic pickup error analysis using this tool in experiments performed with a lead customer, a major automotive tier-1 manufacturer. There are also built-in capabilities that assist root-cause detection, including management of automatic judgement results and countermeasure content tracing.

Figure 2 | pickup error analysis including location and corrective actions.

The power of the underlying platform provides scope to add further analytics tools, such as placement analysis and print analysis. Moreover, the platform is open to leveraging artificial intelligence (AI) in future distributions, which will provide additional analytics capabilities and further accelerate problem solving directly on production lines.


Automation has enabled electronic manufacturers to remove human limitations from many activities on production lines. However, intervention has remained necessary where judgement must be applied and assistance is needed to handle exceptional circumstances and restore correct operation. The latest data-driven dashboard tools provide extra assistance to identify and fix the causes of errors, to help overcome the limitations of operators’ knowledge and shorten the time to restore operation, ultimately enabling further improvement of productivity.

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