PCB manufacturing and assembly is a crucial stage that stands between the design of every technology device and the finished product. Critical business metrics – cost, quality, delivery, etc. – are directly affected by the quality of the manufacturing process. Today, PCB manufacturing performance and productivity are under threat as customers’ delivery requirements become more volatile and pressure on both the engineering and materials infrastructures continues to grow.
In this dynamic environment, successful PCB manufacturing must follow eight steps. This is the first in a two-part series and we will look at four of those steps in each.
Here is the initial quartet:
1.Know your product
2.Do only what needs to be done – and only when it needs to be done
3.Be ready to make anything in any quantity at anytime
4.Know exactly what you are doing at each stage in the process
The second set of steps, covered here in Part Two, is:
1.Stay on top of materials
2.Develop efficient exception management
3.Ensure assurance, conformance, and compliance
4.Deploy seamless operational management
For now, however, I’ll explore each of those first four concepts in more detail.
The manufacturing product model is one of the most significant uncontrolled variables. The late-stage cost of re-spinning a design or implementing countermeasures due to production issues can be several orders of magnitude greater than that if a problem is resolved earlier. Moreover, a delay to new product introduction (NPI) can result in major lost business opportunities if you fail to reach customers on time.
You must accurately and thoroughly understand the PCB and its requirements. The manufacturing processes need to match the product’s requirements in a way that is efficient and that ensures quality. Designs should be checked against manufacturing standards as they arrive for fabrication and before the manufacturing engineering processes begin.
Industry-leading PCB design for manufacturing (DFM) tools mitigate risk and promote product quality. The most advanced DFM tools are based on rules derived from actual process capabilities and configurations. They analyze designs in seconds and then highlight opportunities for cost improvements in manufacture, yield, quality, and testability. Hundreds of tests for PCB fabrication and assembly can be performed that provide clear recommendations to improve a layout improvements, yet without the layout design engineer needing any manufacturing expertise.
Advanced DFM tools use data formats such as ODB++ to represent the complete and accurate manufacturing product model, without that model being weighed down by supporting documentation. Manufacturing receives all the necessary information needed to fabricate the PCB itself and assemble the final product as the designer intends, without the need for data reconstruction.
Traditionally, the first step taken when a new product is introduced to PCB assembly manufacturing is to prepare the design and related data for a specified set of processes. From the production point of view however, rather than an assumed and therefore fixed manufacturing configuration, the manufacturer really needs to prepare several production configurations from which to choose that which best meets the requirements of the customer at a given time. Shopfloor planning needs to determine production times, rates, and quantities for each product, based on this choice of capable production processes that meet delivery requirements. As the number of concurrent discrete products increases and tolerance for finished goods stock decreases — whether in the factory warehouse or a shrinking supply chain — lot sizes have to become smaller and this requires a much higher degree of production interleave than before.
Enterprise resource planning (ERP), manufacturing execution systems, and generic shopfloor optimization software are not that good at finding efficient ways to manage mixed production strategies. They force an unavoidable tradeoff between the flexibility of a higher mix of products against productivity. Planning systems must quickly analyze a project’s shopfloor status, consider changing delivery requirements, and understand PCB process optimization opportunities. That last step requires an ability to survey the project at a high level and simulate material setups, product groupings, within the context of machine and line optimization. The inherent complexity of surface mount technology (SMT) process makes it extremely difficult to achieve these goals.
The inherent complexity of surface-mount technology raises many challenges (Source: Peripitus)
The most common tool used for this process is Microsoft Excel, which can hardly be expected to be able to find the most optimum production plans for SMT. Fortunately, SMT-orientated Production Plan logic is now available that simultaneously optimizes the selection and sequencing of products according to delivery schedules, whilst simultaneously grouping products and feeders throughout the SMT processes.
This approach reduces SMT changeover time and optimizes machine utilization and efficiency. It also creates a production schedule that accurately reflects the needs of the customer, and minimizes stock dormancy in the warehouse and beyond.
The top-level plan is derived from standard ERP tools together with the requirements for each product, which are then broken down for each line and machine. The Production Plan logic is capable of optimization based on real-time customer requirements, the current production status, and the inventory of available materials. Such tools can manage thousands of products over a period of time and perform optimization for the whole shopfloor, applying a flexible set of rules that determines planning policy and priorities.
The result is an immediate increase in operational productivity, with high-mix PCB production achieving levels of efficiency approaching those for high-volume. The ability to respond rapidly and precisely to demand changes means that the factory can be flexible without having to resort to accumulating stock of each of the products or sacrificing performance.
SMT engineers generate production-ready machine programs, test and inspection data, and visual documentation by converting the manufacturing product model data and a local bill of materials (BOM). That BOM usually comes from the ERP system.
This is the first step taken at electronic manufacturing service (EMS) companies, where an understanding of the cost of PCB production is required, along with any specific physical project requirements (e.g., safety-critical requirements for automotive applications).
Carrying out complex process preparation can be very difficult. It starts with the product data qualification and merger of the local BOM data. This step often encounters discrepancies that must be resolved before other processes can start. It is important to get a full understanding any new materials that are being used (e.g., how they are supplied and what sizes and shapes are available, etc.).
Then the SMT assembly work has to be split across different machines in any specified configuration. These machines may run on different software platforms or come from different equipment vendors. SMT-related processes (e.g., screen printers, reflow ovens) also need to be set up.
A similar process flow has to be created for each of the test and inspection processes, whether these are manual, automated or a combination of both.
Finally, comes the operator documentation.
Performing all this for each PCB product often consumes the available engineering resources, particularly in a time when the number of products and the product mix is increasing. As a result, defacto assumptions are inevitable, and these typically lead to restrictions that limit each product to a specific line configuration. Therefore, there are effectively very few, if any choices, about which SMT line is assigned to any product.
Frequently to make life easier, many manufacturing lines will have the same configuration, eliminating any choices in the production rates that can be achieved. This leads to a situation where some lines frequently build to stock not required for delivery, while other lines stand idle. Delivery targets for some products become unachievable.
This is changing thanks to advanced Process Preparation tools. They take the design data and merge the BOM within a graphical interface, allowing discrepancies to be quickly identified and resolved to create a single product dataset.
These tools can generate optimized SMT program sets, test programs, inspection data and more. They can identify all the necessary PCB manufacturing engineering process steps across equipment from multiple vendors. Direct outputs to SMT machines, testers, and inspection machines can be sent without manual data manipulation, using sophisticated automated native program and library generation tools.
All engineering processes share a common-parts-shape data source, linked with the ODB++ product model data and the web-based shape library. Simulation of the SMT machine operation is performed in software to correct placement rotation and offset errors, removing the need for physical product qualification, and thus avoiding line downtime for NPI qualification.
The SMT programming team can now respond to the needs of planning and provide multiple line configurations for each product. That means that PCB production flows can now easily be matched to delivery timetables because alternate configurations can be prepared in just a couple of minutes
The results include reduced NPI lead-time, increased asset utilization, the elimination of line down-time for product qualification, and a reduction in the engineering effort to duplicate data maintenance across different systems. Overall, there are general increases in machine optimization, line balance, test coverage, reliability and yield, and assembly operation.
SMT machines are now very fast, and SMT materials have become very small. It is impossible to follow the operation of SMT machines with the naked eye. Multiply the inherent challenge here by the number of machines across all the lines on the shopfloor. Now ask yourself how can even the most experienced industrial engineer be expected to diagnose and explain sudden drops in performance or find the causes of unexpected quality issues using traditional inspection techniques.
This affects both the reliability of on-time delivery of products, and stresses the associated production resources and materials supply chains because they cannot be synchronized effectively to requirements. Planning changes required to meet changing demands can be very risky to execute because of all the unknowns that need to be assessed. Materials will have been physically committed to production in terms of kit preparation; work-orders may be partially completed with associated part-built work-in-progress at several locations.
The true utilization rate of equipment is also often unknown: State-of-the-art machines incorporate multiple heads, multiple conveyors, and multiple modular stages, and this combination can hide significant avoidable idle time. Also, the timing of changeovers between products cannot be predicted accurately which creates bottlenecks. These percolate right through to issues such as which operator performs which task. Reports created using data extracted from individual machines have little meaning because they do not consider the full context of events, specifically the effects of external causes of stoppages.
The situation is so dismal, that manual data collection or simple PCB counting is still often the norm. Data from the SMT production process generally has minimal value. It is inaccurate, incomplete, unqualified, and arrives too late to be acted upon. All this creates a huge limitation for successful productivity improvement initiatives, planning optimization, material delivery, and resource management.
Here again, the introduction of advanced capabilities is providing new approaches that can collect and process data in real-time no matter what type or vendor of SMT machine or related process, including manual operations. Events and supporting data are read and normalized, eliminating differences in the data format and meaning, and harmonized for a single common language. Data collected is automatically qualified.
For example, when a machine stops, the production line can be analyzed to see why the flow of PCBs has stopped, or why the output conveyor is blocked. So, the occurrence and cost of any event during production can be accurately attributed. Information about complex SMT processes (e.g., under-utilization of modules or heads) is recorded and this exposes opportunities to improve productivity. Event data collected even includes the precise usage and spoilage of materials so that accurate material consumption can be reported.
As the data is collected and processed live in real-time, it can be utilized by many of the key operational and control functions. Use cases include the data’s exploitation by asset management to increase productivity, by material management for JIT delivery of materials to the line, and by production planning to implement changes that are exactly based on the current production commitment. This leads to an increase in productivity, improved reliability for on-time delivery, reduced on-site finished goods storage, and better planning change execution that follows customer requirements.
This brings us to the end of our review of the first four necessary steps for cost-effective, high quality PCB manufacturing and assembly. Now read on to the second part of this overview, where we take a detailed look at the next four steps:
1.Stay on top of materials
2.Exercise exception management
3.Enforce assurance, conformance, and compliance
4.Employ seamless operational management
Michael Ford is Senior Marketing Development Manager in the Valor Division of Mentor Graphics.
Having majored in Electronics, Michael started his career with Sony, gaining a combination of hardware, software, system architecture and manufacturing skills, leading to the creation and management of Sony’s global Lean Manufacturing solutions in Japan.
Since joining Mentor Graphics in 2008, Michael has become a key contributor to thought leadership in the industry, predicting trends and bringing insights on opportunities that can be gained by customers, driving the evolution of manufacturing execution technologies to deliver direct business benefits.