Reducing Cycle Time in Electronic Device Assembly Lines

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In today’s competitive manufacturing landscape, reducing cycle time in electronic device assembly lines has become a critical priority for companies seeking to enhance productivity, lower operational costs, and maintain market competitiveness. This comprehensive case study examines proven strategies and methodologies that manufacturers can implement to achieve significant cycle time reductions while maintaining or improving product quality.

Understanding Cycle Time in Electronic Assembly Manufacturing

Cycle time is the total time required to produce one unit, from receiving raw materials to delivering the finished product. In electronic device assembly, this metric serves as a fundamental performance indicator that directly impacts production capacity, delivery schedules, and overall operational efficiency. It differs from Takt Time, which is the rate at which a product needs to be produced to meet demand, and Lead Time, which includes the full time from order to delivery.

A longer-than-expected cycle time leads to reduced productivity and increased operational costs. For electronics manufacturers, where product lifecycles are short and market demands fluctuate rapidly, the ability to minimize cycle time provides a decisive competitive advantage. Reduced cycle time means lower lead times and faster delivery to meet customer demand. When a company reduces lead time and delivers its product faster, new and repeat orders are more likely.

The Business Case for Cycle Time Reduction

Financial Impact and ROI

As cycle time drops, efficiency and productivity rise. Cumulatively, these changes lower the cost per unit produced. Individually, labor utilization reduces due to automated processes, and the elimination of waiting time adds money to the bottom line. The financial benefits extend beyond direct cost savings to include improved asset utilization and return on investment.

A 25% reduction in cycle time means the company has unlocked more capacity and will be more productive. As cycle time is reduced, overall equipment effectiveness is increased. This reduction helps produce more jobs with the same resources, ensuring ROI on expensive manufacturing equipment. For capital-intensive electronics manufacturing operations, this improvement in equipment effectiveness can translate to millions of dollars in avoided capital expenditures.

Competitive Advantages

Reducing cycle time gives companies a competitive advantage, which comes in two forms. First, as mentioned above, reducing cycle time means that companies reduce lead times by turning around finished goods faster. This reduction can give them a market advantage as the “go-to” source. In the fast-paced electronics industry, being able to respond quickly to market demands and customer orders can be the difference between winning and losing business.

Second, reducing cycle time allows companies to reduce lead time and innovate new products faster. With new offerings entering the market more quickly than the competition, companies realize a marketing advantage. This agility is particularly valuable in consumer electronics, where product refresh cycles continue to accelerate.

Comprehensive Case Study: Electronics Assembly Line Optimization

Initial Assessment and Baseline Measurement

The featured company, a mid-sized electronics manufacturer specializing in consumer electronic components, faced increasing pressure to improve delivery times while maintaining competitive pricing. Before optimization, their average cycle time was 120 seconds per unit—slowing production and increasing delivery times. This baseline measurement was established through comprehensive time studies and data collection across all assembly stations.

To optimize assembly line efficiency, industrial engineers engage in a thorough examination of the existing processes. This initial analysis is crucial, as it establishes a baseline for identifying areas requiring improvement. The company employed multiple analytical techniques to understand their current state, including value stream mapping, bottleneck analysis, and detailed time studies at each workstation.

Identifying Bottlenecks and Constraints

Bottleneck analysis focuses on identifying points within the assembly line where the flow of work is impeded. These bottlenecks can significantly affect the overall throughput of the system. In this case study, the analysis revealed several critical constraint points that were limiting overall production capacity.

Bottlenecks: When specific machines or workstations take more time than others, they slow down the entire production flow. The company discovered that their printed circuit board assembly (PCBA) station was operating at capacity while upstream and downstream processes had significant idle time. An unbalanced line always has a bottleneck — one station that takes longer than every other station on the line. While that bottleneck station works, every downstream station sits idle waiting for the next unit. Every upstream station finishes early and has nothing to do. That idle time represents wasted labor, wasted floor space, and lost production capacity.

The bottleneck analysis also identified several types of constraints:

  • Equipment bottlenecks: Equipment bottlenecks are typically associated with equipment downtime, operator response time, etc.
  • Resource bottlenecks: Resource bottlenecks include demand for utilities, labor, and raw materials.
  • Process bottlenecks: Inefficient workflows and unnecessary process steps that added no value
  • Material flow bottlenecks: Delays in component availability and inventory management issues

Strategic Implementation: Key Improvement Initiatives

1. Workflow Streamlining and Process Optimization

One of the primary techniques employed for this purpose is value stream mapping. This method involves creating a visual representation of the flow of materials and information throughout the assembly line. By mapping the entire process, engineers can pinpoint waste, redundancies, and delays that hinder overall productivity.

The company conducted a comprehensive value stream mapping exercise that revealed numerous non-value-added activities. The cornerstone of lean is identifying and eliminating “muda” – any activity that consumes resources without adding value to the final product. In assembly lines, this might include: Excessive Movement: Operators constantly searching for parts, tools, or instructions waste valuable time. Streamline workstation layout and implement visual management techniques to minimize unnecessary movement.

Specific workflow improvements included:

  • Eliminating redundant quality inspection steps by implementing in-process verification
  • Reducing operator walking distances through strategic workstation layout redesign
  • Standardizing work procedures across all shifts to eliminate variation
  • Implementing visual management systems for faster decision-making
  • Removing unnecessary documentation and approval steps

2. Assembly Line Balancing

Line balancing is the process of distributing work elements across stations on an assembly line so that each station takes approximately the same amount of time to complete its assigned tasks. The objective is straightforward: minimize idle time, maximize throughput, and meet customer demand with the fewest stations possible.

Station balancing ensures a balanced workload across all assembly stations where each station operates efficiently and contributes equally to the overall production flow. The company performed detailed time studies at each workstation to understand the actual work content and identify imbalances.

List every task required to assemble the product. Each task should be the smallest practical unit of work that cannot reasonably be further divided. For a typical electromechanical assembly: Record the time for each element through time studies, video analysis, or predetermined motion time systems (PMTS). Use multiple observations to account for normal variation. A single measurement is not reliable enough to base your balance on.

The line balancing initiative resulted in:

  • Redistribution of tasks to eliminate the primary bottleneck station
  • Reduction of idle time across all workstations by 18%
  • Improved operator utilization from 72% to 89%
  • More consistent flow of work-in-process inventory

3. Automation Implementation for Repetitive Tasks

After a detailed process analysis, automation implementation, and integration of dynamic scheduling with JITbase, the company reduced its cycle time to 90 seconds per unit. Key improvements included optimizing the CNC program, which led to a 30% reduction in machining time, and automating part loading/unloading with a robotic arm.

The automation strategy focused on high-volume, repetitive tasks that offered the greatest return on investment. Key automation initiatives included:

  • Automated component placement: Implementation of pick-and-place robots for surface mount technology (SMT) operations
  • Automated optical inspection (AOI): reduce their AOI false calls by up to 60%, while also increasing throughput on the line.
  • Robotic material handling: Implementing Conveyor Systems: Conveyor belts can automate the transportation of parts between stations, eliminating the need for manual handling and ensuring a consistent flow of materials.
  • Automated testing equipment: Integration of automated functional testing to replace manual testing procedures

By using our trained Artificial Intelligence (AI) algorithm, you’ll be able to improve your productivity through continuous improvement of each machine’s cycle time (CT). Our AI algorithm uses machine learning (ML) capabilities to learn a baseline pattern for each product on each machine over time. Then, it will automatically detect/predict CT anomalies and issue alerts. These alerts will give you the chance to quickly identify bottlenecks so you can take corrective action on the root cause and quickly clear identified bottleneck. This results in reduced time responding to problems, as well as a proactive problem-solving methodology.

4. Optimized Inventory and Material Management

To help reduce cycle times within the cell, a continuous improvement project was undertaken to improve the material flow process. A current state analysis of the process showed an opportunity to improve process standardization and prioritization while lowering inventory levels.

Material availability and inventory management emerged as significant contributors to cycle time delays. The company implemented several strategies to optimize material flow:

  • Kanban system implementation: The Kanban system utilizes visual cues like cards or bins to signal material replenishment needs. This helps maintain optimal stock levels at each station, preventing delays caused by material shortages.
  • Point-of-use storage: Relocating component inventory closer to assembly stations to reduce retrieval time
  • Supplier integration: Working with key suppliers to implement just-in-time delivery schedules
  • Inventory optimization: Reducing work-in-process inventory levels while maintaining production flow
  • Material handling optimization: In an assembly line, efficient material handling ensures a smooth flow of parts and components between stations, preventing delays and keeping the production process in perfect rhythm.

5. Comprehensive Operator Training and Development

Recognizing that technology alone cannot drive sustainable improvements, the company invested significantly in workforce development. The training program encompassed multiple dimensions:

Technical Skills Enhancement:

  • Cross-training operators on multiple workstations to improve flexibility
  • Advanced training on new automated equipment and systems
  • Quality control and inspection technique training
  • Troubleshooting and basic maintenance skills development

Lean Manufacturing Principles:

  • Lean manufacturing isn’t just a philosophy; it’s a powerful toolkit for streamlining assembly lines and reducing cycle times. By embracing its core principles, you can eliminate waste, optimize workflows, and empower your workforce to continuously improve efficiency.
  • Training on waste identification and elimination techniques
  • Problem-solving methodologies including root cause analysis
  • Continuous improvement mindset and Kaizen principles

Data-Driven Decision Making:

  • Collect data on cycle times, defect rates, and other key metrics. Analyze this data to identify areas for improvement and measure the effectiveness of implemented changes.
  • Training operators to use real-time production monitoring systems
  • Empowering frontline workers to make data-informed decisions

6. Setup Time Reduction Using SMED Methodology

Changeover time: Inefficient transitions between production batches increase cycle time. Applying the SMED (Single-Minute Exchange of Die) method helps shorten these transitions by standardizing changeover processes. For electronics assembly lines that produce multiple product variants, changeover time represented a significant source of lost productivity.

The SMED implementation focused on:

  • Converting internal setup activities (performed while line is stopped) to external activities (performed while line is running)
  • Standardizing setup procedures across all product types
  • Implementing quick-change tooling and fixtures
  • Creating visual setup guides and checklists
  • Organizing tools and materials for rapid access

These improvements reduced average changeover time from 45 minutes to 12 minutes, enabling more frequent product changes and smaller batch sizes without sacrificing productivity.

Advanced Technologies and Digital Tools

Real-Time Monitoring and Analytics

Cycle Time Analysis (CTA), supported by machine learning algorithms, is being used to improve assembly efficiency across a wide range of industries. CTA can be utilized to identify those bottlenecks that have a significant impact on overall production efficiency of an assembly line. CTA considers various critical parameters: equipment availability, quality rate, Overall Equipment Efficiency (OEE), equipment downtime, operator performance, etc.

The company implemented an integrated manufacturing execution system (MES) that provided real-time visibility into production performance. Accurately tracking cycle time loss provides your plant floor team with insights on how to increase manufacturing speed. Establish accurate Ideal Cycle Times, differentiate between slow cycles and small stops, and use this data during the shift to create positive change.

Key features of the digital monitoring system included:

  • Real-time cycle time tracking for each workstation
  • Automated alerts for cycle time deviations
  • Digital dashboards displaying key performance indicators
  • Historical trend analysis and reporting capabilities
  • Integration with quality management systems

Artificial Intelligence and Machine Learning Applications

While the ideal cycle time is typically determined manually, machine learning algorithms can be used to automatically identify and analyze deviations and bottlenecks. This process requires training the AI/ML model with real time data gathered during production cycles and quantifying acceptable variances. Once deployed, these models can quickly improve CTA and significantly reduce the time required to spot bottlenecks at different machines/stations.

The AI-powered systems provided several advantages:

  • Predictive maintenance scheduling to prevent unplanned downtime
  • Dynamic bottleneck detection and alerting
  • Optimization of production scheduling based on real-time constraints
  • Quality prediction and defect prevention
  • Continuous learning and improvement of cycle time baselines

One of the best strategies to reduce bottlenecks is with Artificial Intelligence. Using AI-powered tools can help in the easy and seamless identification of bottlenecks. You can completely eliminate bottlenecks with AI tools where predictive analytics, real-time monitoring, and accurate demand forecasting can collaboratively improve production efficiencies, making the entire process, more responsive and agile.

Lean Manufacturing Integration

Applying Lean Principles to Electronics Assembly

The integration of lean manufacturing tools in assembly operations has demonstrated consistent success in improving productivity, reducing cycle time, and enhancing operational flow across different industries. The company embraced lean manufacturing as an overarching philosophy to guide all improvement activities.

Using lean tools such as waste identification and the ECRS (Eliminate, Combine, Rearrange, Simplify) method, several short-term improvements were implemented. These modifications significantly reduced cycle times, rebalanced workload distribution, and improved ergonomics.

The ECRS methodology provided a structured approach to process improvement:

  • Eliminate: Remove non-value-added activities entirely
  • Combine: Merge related tasks to reduce handoffs and transitions
  • Rearrange: Optimize the sequence of operations for better flow
  • Simplify: Reduce complexity in remaining tasks

Continuous Improvement Culture

Results demonstrate that even low-cost, incremental changes through Kaizen can yield measurable gains in productivity and quality. The company established a formal continuous improvement program that engaged employees at all levels.

Encourage collaboration between operators, maintenance personnel, and engineers to identify and implement improvements throughout the assembly line. Regular Kaizen events brought together cross-functional teams to tackle specific improvement opportunities, fostering a culture of continuous learning and innovation.

Key elements of the continuous improvement program included:

  • Weekly gemba walks by leadership to observe processes firsthand
  • Monthly Kaizen events focused on specific improvement opportunities
  • Employee suggestion system with rapid implementation of viable ideas
  • Visual management boards tracking improvement metrics
  • Recognition and reward programs for improvement contributions

Measuring Success: Results and Outcomes

Quantitative Results

After implementing the comprehensive cycle time reduction program over a 12-month period, the company achieved remarkable results:

Cycle Time Improvements:

  • Overall cycle time reduced from 120 seconds to 90 seconds per unit (25% reduction)
  • Bottleneck station cycle time reduced by 35%
  • Average changeover time reduced from 45 minutes to 12 minutes (73% reduction)
  • Work-in-process inventory reduced by 40%

Productivity and Capacity Gains:

  • As a result, the company increased its OEE by 15% and cut production costs by 10%.
  • Daily production capacity increased from 400 units to 533 units (33% increase)
  • Labor productivity improved by 28%
  • Equipment utilization increased from 68% to 85%

Quality and Delivery Performance:

  • First-pass yield improved from 94% to 98%
  • On-time delivery performance increased from 82% to 96%
  • Customer lead time reduced from 3 weeks to 2 weeks
  • Defect rate reduced by 45%

Qualitative Benefits

Beyond the measurable metrics, the company experienced several qualitative improvements:

  • Enhanced employee engagement: Operators reported higher job satisfaction due to reduced frustration with process inefficiencies and greater involvement in improvement activities
  • Improved workplace safety: Ergonomic improvements and reduced material handling resulted in fewer workplace injuries
  • Better customer relationships: Faster response times and improved delivery reliability strengthened customer partnerships
  • Increased organizational agility: The ability to quickly adapt to changing product mix and volume requirements
  • Knowledge development: Building internal expertise in lean manufacturing and continuous improvement methodologies

Financial Impact

The cycle time reduction initiative delivered substantial financial returns:

  • Cost savings: Annual operating cost reduction of $1.2 million through improved labor productivity and reduced waste
  • Revenue growth: Additional $2.5 million in annual revenue from increased capacity without capital investment
  • Avoided capital expenditure: Eliminated the need for a planned $3 million facility expansion
  • Inventory reduction: Released $800,000 in working capital through work-in-process inventory reduction
  • Return on investment: Achieved 340% ROI on improvement initiative costs within the first year

Implementation Challenges and Lessons Learned

Common Obstacles

The journey to cycle time reduction was not without challenges. Understanding these obstacles can help other organizations prepare for similar initiatives:

Resistance to Change: Initial skepticism from experienced operators who were comfortable with existing processes required extensive communication and involvement in the improvement process to overcome.

Data Quality Issues: Some manufacturing facilities may have real-time data tracking software, such as a material requirements planning (MRP) system, to measure and track cycle time. However, there is no system that can tell you what your ideal cycle times should be. These systems can only report what the cycle time is at any given point in time. They typically do not contain the embedded intelligence necessary to identify your ideal cycle time or to tell you how to get there. Establishing accurate baseline measurements required significant effort to improve data collection systems.

Resource Constraints: Balancing improvement activities with ongoing production demands required careful planning and phased implementation.

Technical Complexity: Integrating new automation and digital systems with legacy equipment presented technical challenges that required creative solutions.

Critical Success Factors

Several factors proved critical to the success of the cycle time reduction initiative:

Leadership Commitment: Visible and sustained support from senior leadership provided the resources and organizational focus necessary for success.

Cross-Functional Collaboration: Breaking down silos between engineering, operations, quality, and maintenance enabled holistic problem-solving.

Data-Driven Approach: Basing decisions on objective data rather than assumptions ensured improvements targeted the right areas.

Phased Implementation: Rolling out changes incrementally allowed for learning and adjustment while maintaining production stability.

Employee Involvement: Engaging frontline workers in problem identification and solution development ensured practical, sustainable improvements.

Sustainability Strategies

To ensure improvements were sustained over time, the company implemented several mechanisms:

  • Standard work documentation: Capturing best practices in detailed standard operating procedures
  • Regular audits: Periodic reviews to ensure adherence to improved processes
  • Performance monitoring: Ongoing tracking of key metrics with rapid response to deviations
  • Continuous training: Regular refresher training and onboarding of new employees on improved processes
  • Management review: Monthly leadership reviews of improvement metrics and new opportunities

Best Practices for Cycle Time Reduction in Electronics Assembly

Assessment and Planning Phase

1. Establish Clear Baseline Metrics

The first step in CTA is to define the ideal cycle time. The ideal cycle time will be the time required to complete a job with no downtime, no work stoppages, and no flaws. Document current performance comprehensively before beginning improvement activities.

2. Conduct Comprehensive Process Analysis

Use multiple analytical tools including value stream mapping, time studies, and bottleneck analysis to understand current state thoroughly. Industrial engineers utilize various metrics such as cycle times, throughput rates, and resource utilization rates to determine where these bottlenecks occur.

3. Prioritize Improvement Opportunities

Focus initial efforts on constraints that will deliver the greatest impact. In many cases, cycle time can be improved through the identification and removal of bottlenecks. Use data to prioritize rather than relying on intuition alone.

Implementation Phase

4. Start with Quick Wins

Build momentum and credibility by implementing low-cost, high-impact improvements first. This demonstrates value and builds support for larger initiatives.

5. Balance Technology and Process Improvements

While automation can deliver significant benefits, don’t overlook process improvements that require minimal investment. Often the greatest gains come from eliminating waste and optimizing workflows.

6. Implement Robust Change Management

Communicate clearly about why changes are being made, involve affected employees in the improvement process, and provide adequate training and support.

Sustainment Phase

7. Monitor Performance Continuously

Automated systems compare each manufacturing cycle to the Ideal Cycle Time and calculate the cycle time loss for each and every part produced: Cycle Time Loss = Run Time – (Total Parts x Ideal Cycle Time) In order to measure cycle time loss accurately it is important to automate data capture and to follow a clearly defined measurement standard that is consistently applied over time and across equipment.

8. Foster Continuous Improvement Culture

Cycle time reduction is not a one-time project but an ongoing journey. Establish systems and culture that support continuous identification and implementation of improvements.

9. Share Knowledge and Best Practices

Document lessons learned and successful approaches. Share knowledge across production lines and facilities to multiply the impact of improvements.

Industry-Specific Considerations for Electronics Manufacturing

High-Mix, Low-Volume Environments

Electronics manufacturers often face the challenge of producing many different product variants in relatively small quantities. This requires:

  • Flexible manufacturing systems that can quickly adapt to different products
  • Minimized changeover times through SMED and quick-change tooling
  • Modular workstation designs that can be reconfigured easily
  • Digital work instructions that can be updated rapidly for different products

Quality and Reliability Requirements

Electronics products often have stringent quality and reliability requirements. Cycle time reduction efforts must not compromise quality:

  • Implement robust error-proofing (poka-yoke) devices
  • Use automated inspection systems to maintain quality while reducing inspection time
  • Establish clear quality gates that cannot be bypassed
  • Monitor quality metrics closely during and after improvement implementation

Cleanroom and ESD Requirements

In cleanroom actuator assembly lines—where environmental controls, process precision, and space limitations are critical—such tools become even more essential. Special considerations for controlled environments include:

  • Material flow optimization to minimize contamination risk
  • Ergonomic considerations within the constraints of protective equipment
  • Automation solutions compatible with cleanroom requirements
  • Efficient use of limited cleanroom space

Industry 4.0 and Smart Manufacturing

The evolution toward Industry 4.0 is creating new opportunities for cycle time reduction through:

  • Digital twins: Virtual replicas of production systems enabling simulation and optimization before physical implementation
  • Internet of Things (IoT): Connected sensors providing unprecedented visibility into equipment and process performance
  • Advanced analytics: Big data analysis revealing patterns and opportunities not visible through traditional methods
  • Cyber-physical systems: Integration of computational and physical processes for autonomous optimization

Artificial Intelligence Advancement

The implementation of CTA can help manufacturing facilities improve overall production, lower costs, increase quality, reduce downtime, and refine process improvement initiatives. Efforts associated with manual data entry and analysis can be significantly reduced by implementing machine learning models resulting in improved employee efficiency and reduced overhead costs.

AI and machine learning will continue to advance, offering:

  • More sophisticated predictive capabilities
  • Autonomous optimization of production parameters
  • Real-time adaptive scheduling and resource allocation
  • Enhanced quality prediction and defect prevention

Collaborative Robotics

Collaborative robots (cobots) that can work safely alongside human operators are enabling new approaches to automation:

  • Flexible automation that can be deployed and redeployed quickly
  • Augmentation of human capabilities rather than full replacement
  • Lower cost of entry for automation in smaller operations
  • Easier integration into existing production lines

Practical Implementation Roadmap

Phase 1: Assessment and Planning (Months 1-2)

  • Form cross-functional improvement team
  • Conduct comprehensive baseline assessment
  • Perform value stream mapping and bottleneck analysis
  • Identify and prioritize improvement opportunities
  • Develop detailed implementation plan with timeline and resources
  • Establish key performance indicators and targets

Phase 2: Quick Wins (Months 3-4)

  • Implement low-cost, high-impact improvements
  • Eliminate obvious waste and non-value-added activities
  • Optimize workstation layouts and material flow
  • Standardize work procedures
  • Implement visual management systems
  • Begin operator training on lean principles

Phase 3: Major Improvements (Months 5-9)

  • Implement line balancing improvements
  • Deploy automation for high-impact applications
  • Optimize inventory and material management systems
  • Implement SMED for changeover reduction
  • Deploy real-time monitoring and analytics systems
  • Conduct advanced operator training

Phase 4: Optimization and Sustainment (Months 10-12)

  • Fine-tune improvements based on performance data
  • Document standard work and best practices
  • Establish continuous improvement processes
  • Implement performance monitoring and management systems
  • Conduct lessons learned review
  • Plan next phase of improvements

Conclusion

Reducing cycle time in electronic device assembly lines represents a powerful opportunity for manufacturers to improve competitiveness, reduce costs, and enhance customer satisfaction. As demonstrated in this comprehensive case study, a 25% reduction in cycle time is achievable through a systematic approach combining process optimization, automation, lean manufacturing principles, and workforce development.

Reducing cycle time is a powerful lever to enhance industrial efficiency and lower production costs. By integrating methods like Lean Manufacturing, automation, and live scheduling, manufacturers can reduce waste and improve their OEE. The key to success lies not in any single technique but in the comprehensive integration of multiple improvement strategies tailored to the specific challenges and opportunities of each operation.

In the high-pressure world of manufacturing, every second counts. Delays caused by misplaced parts, machine malfunctions, or rework eat away at profits and throttle production. Here’s where conquering cycle time becomes your strategic weapon. By streamlining processes and minimizing these delays, you can supercharge throughput, delight customers with faster deliveries, and optimize resource utilization. Ultimately, conquering cycle time is the key to streamlining operations and becoming a manufacturing mastermind.

Organizations embarking on cycle time reduction initiatives should remember that this is a journey rather than a destination. The most successful companies view cycle time optimization as an ongoing process of continuous improvement, constantly seeking new opportunities to eliminate waste, enhance efficiency, and deliver greater value to customers.

By following the strategies, methodologies, and best practices outlined in this case study, electronics manufacturers can achieve similar or even greater results. The combination of data-driven analysis, proven improvement methodologies, advanced technologies, and engaged employees creates a powerful foundation for sustainable competitive advantage in today’s demanding manufacturing environment.

For more information on manufacturing optimization strategies, visit the Lean Enterprise Institute or explore resources from the American Society for Quality. Additional insights on electronics manufacturing best practices can be found through the IPC – Association Connecting Electronics Industries.