Forensic Engineering Investigation of Electrical and Electronic Causes of an Industrial Equipment Failure

This case involved industrial equipment whose repeated, seemingly random failures resulted in the buyer of that equipment suing the seller. The failures had been isolated to a group of several transistors within electro-mechanical modules within the equipment, but the root cause of those transistors failing had not been determined. The equipment seller had more than 1,000 units in the field with no similar failures. And the electro-mechanical module manufacturer had more than 20,000 units in the field with no similar failures. Electrical contractors hired by the buyer had measured power quality, and reported no faults found in the three-phase power at the equipment terminals. This paper presents circuit analyses of the failing electro-mechanical module, basics of electrostatic discharge damage and protection, and the root cause of these failures — an electrical code-violating extraneous neutral-to-ground bond in a secondary power cabinet.

Data-driven Assessment of Market Share Growth Factors of Union Electrical Contractors in the U.S.

Building trade unions have had an instrumental role in advocating for worker welfare, training, health and safety in the U.S. construction industry. Since 1970s, the membership and market share of trade unions have dramatically declined, and there is no clear understanding and previous scholarly assessment of the drivers of such decline. This study provides a data-driven assessment of the market share controlling factors of the U.S. electrical trade unions and their signatory contractors. The study depended on collecting a large amount of data from the union electrical contractor organization, government census agencies, surveys, and interviews of electrical contractors. Union market share trends were found to be correlated to the use of higher crew ratios and the adoption of non-apprenticeship worker classifications.

Nature of Occupational Incidents among Electrical Contractors

Electrical contractors have experienced a rise in occupational fatalities in recent years. In 2017, electrical contractors also had the second highest number of non-fatal injuries among specialty trade contractors. Identifying statistically significant dependencies between these catastrophic outcomes and a handful of well-defined contributing factors in construction accidents offers a first step in mitigating the risks of construction accidents in this trade. Therefore, this study used methodologies of descriptive and quantitative statistics to identify the contributing factors most affecting occupational accident outcomes among electrical contracting enterprises, given an accident occurred. Accident reports were collected from the Occupational Safety and Health Administration’s fatality and catastrophe database. To ensure the reliability of the data, the team manually codified more than 600 incidents through a comprehensive content analysis using injury-classification standards. Inclusive of both fatal and non-fatal injuries, the results showed that most accidents happened in nonresidential buildings, new construction, and small projects (i.e., $50,000 or less). The main source of injuries manifested in parts and materials (46%), followed by tools, instruments, and equipment (19%), and structure and surfaces (16%). The most frequent types of injuries were fractures (31%), electrocutions (27%), and electrical burns (14%); the main injured body parts were upper extremities (25%), head (23%), and body system (18%). Among non-fatal cases, falls (37%), exposure to electricity (36%), and contact with objects (19%) caused most injuries; among fatal cases, exposure to electricity was the leading cause of death (50%), followed by falls (28%) and contact with objects (19%). The analysis also investigated the impact of several accident factors on the degree of injuries and found significant effects from such factors such as project type, source of injury, cause of injuries, injured part of body, nature of injury, and event type. In other words, the statistical probability of a fatal accident—given an accident occurrence—changes significantly based on the degree of these factors. Beyond these outcomes, the described content-analysis methodology contributes to the accident-analysis body of knowledge by providing a framework for codifying data from accident reports to facilitate future analysis and modeling attempts (e.g., developing logistic regression models) to subsequently mitigate more injuries in other fields.