Is there a single approach to harmonizing MES and traceability procedures?
The electronics manufacturing services industry is a form of controlled chaos. Each factory supports multiple customers in multiple industries with a variety of regulatory, industry-specific and company-specific data collection requirements. Demand among programs also varies. Some programs may be high volume and very predictable, while others have varying demand or high product mix. Not surprisingly, most EMS companies address these challenges with a combination of third-party and internally developed systems that automate data collection and analysis. This effort to address a wide range of evolving customer requirements can drive system redundancies over time, however, particularly when an EMS company has multiple facilities.
From a Lean perspective, a streamlined approach with standardized equipment and processes both inter- and intra-facility is desirable because standardization minimizes the non-value-added work driven by variation and can increase available capacity in automated processes. The challenge when standardizing internally developed software among multiple EMS facilities is that often the needs of a particular group of customers influence internally developed system design at each facility. Consequently, focus on system standardization among facilities often requires focus on process standardization as well.
Cutting time-to-market and shipping errors using Lean principles.
OEMs “new to outsourcing” represent a special challenge for electronics manufacturing services providers because often their systems and processes are not as defined and documented as those of companies that regularly work with EMS partners. Nevertheless, such OEMs also represent the segment of EMS customers able to leverage the most value from a successful outsourcing partnership, provided the EMS company properly sets expectations. Lean manufacturing philosophy’s focus on process improvement and elimination of non-valued-added activity provides an excellent roadmap in this expectation-setting process.
The seven wastes provide ample guidelines for areas of improvement in transitioning new-to-outsourcing projects:
Simple fixes are often the best solution for small variances.
In a perfect world, manufacturing process setup should eliminate the potential for mistakes. In practice, however, process complexity and the impact of system variation makes that impossible. Consequently, organizations committed to the efficiencies of Lean manufacturing often use a range of tools to identify and eliminate defect opportunities from their process.
SigmaTron International’s Tijuana, Mexico, facility uses a number of these tools in this process. During project launch, advanced product quality planning (APQP) failure mode and effects analysis (FMEA) is used to set up the most efficient, defect-free process. The product part approval process (PPAP) is used on automotive projects to validate the process, while customer-specific validation processes are used for projects in other industries. Once production is ongoing, statistical process control (SPC) and other forms of quality data collection and monitoring are utilized to monitor processes and track defects. When defects occur, a kaizen event is scheduled, and tools such as 8D problem-solving, Six Sigma’s Define-Measure-Analyze-Improve-Control (DMAIC) and poka yoke are applied to analyze and correct the root cause.
Eliminate variation that causes inefficiency or defects, while maintaining flexibility to scale.
A configure-to-order assembly process helps reduce finished goods inventory and enhance scheduling flexibility. However, it also introduces variation in the production process. Use of Lean manufacturing principles in designing production flow can ensure efficiency and minimize the defect opportunities this level of variation could otherwise create.
SigmaTron International’s facility in Acuna, Mexico, has a dedicated assembly and test “focused factory” area to provide configure-to-order (CTO) services for a manufacturer of industrial products. The customer has outsourced over 50 different product types that are a mix of legacy and current product.
Design for manufacturability (DfM) analysis is performed during the new product introduction (NPI) phase to identify potential issues prior to the product entering production. Test strategy and programming development is conducted for new products, and test programming is optimized for legacy products, where needed.
But don’t obsess over the distribution.
Yes, I said it. Normal data are nearly never normal.
In Six Sigma classes we study outliers, shift, drift and special cause events. But what we don’t always consider is that these “unexpected” data points may be part of the process and not as rare as we think.
First, let’s look at a set of screw torque data. The chart in FIGURE 1 is for a set of screw torques taken sequentially from a “smart” driver. We can see the data are normal (p=0.895), and the histogram and time series plot back that up.