Questions to ask before action is taken.

Most who perform statistical analyses that guide organizations to solve problems do not have advanced degrees in statistics. We’ve attended classes at university, engaged in varying levels of Six Sigma training, or conducted self-study.

But I think it is safe to say we all have learned that statistically evaluating a set of data is complicated and rife with uncertainty. We choose among many possible statistical tools, and numbers “pop” out telling us if our hypothesis is correct. From those data, we proceed to either take an action or not take an action, depending on the statistical results.

Yet how many finish an analysis and wonder what if it is wrong? Did I have enough data?  Did I choose the proper statistical tool? Do I even know the proper statistical tool? Arghh! (I suspect doctors of statistical science also have “arghh” moments.)

To continue reading, please log in or register using the link in the upper right corner of the page.

Striking the right balance between costs and cycle time.

Decisions made in product design can impact assembly cost, defect opportunities and inventory cost. While design for manufacturability (DfM) analysis can eliminate many issues, less commonly analyzed decisions related to cost targets, scheduling and work team assignments can have unintended consequences that generate unacceptable levels of waste.

Lean manufacturing practitioners are aware of Taiichi Ohno’s concept of the seven wastes (muda) in manufacturing as part of the Toyota Production System (TPS). To recap, those seven wastes are:

1. Waste of overproducing (no immediate need for product being produced).
2. Waste of waiting (idle time between operations).
3. Waste of transport (product moving more than necessary).
4. Waste of processing (doing more than what is necessary).
5. Waste of inventory (excess above what was required).
6. Waste of motion (any motion not necessary outside of production).
7. Waste of defects (producing defects requiring rework).

To continue reading, please log in or register using the link in the upper right corner of the page.

Leveraging the IT department to reduce operation-caused variation.

One continuing trend in electronics manufacturing services is the increasing role IT-related solutions have in supporting a Lean manufacturing-driven organizational culture. This is particularly true of proprietary solutions that automate processes in ways that minimize normally occurring variation or help eliminate non-value-added activity.

One example of this is SigmaTron International’s proprietary Manufacturing Execution System (MES) system known as Tango, whose Phase III system went live at the EMS company’s Elk Grove Village (IL) facility in June. The overarching goal of Tango is to centralize tools used throughout the company for production management, while adding enough flexibility via customization to address facility-specific or customer-specific situations.

System strategies and the visual factory can handle rapid changes in demand.

Supply-chain disruption and Lean philosophy rarely go hand-in-hand. In some cases, however, systems created to support Lean manufacturing or principles themselves help mitigate the chaos the pandemic has created in the global supply chain.

SigmaTron has operations in the US, Mexico, China and Vietnam. As a result, we had a bird’s-eye view of the initial impact on manufacturing operations in China and used that as a roadmap for preparing operations in other locations for disruption, along with best in-plant practices for disease mitigation. While the ways different jurisdictions reacted to Covid-19 varied, the issues were somewhat similar. This column looks at some lessons learned in that process from this contract manufacturer’s perspective.

To continue reading, please log in or register using the link in the upper right corner of the page.