Why Elevators Essentially Never Free-Fall: Engineering Safety

The design philosophy that has made aviation so safe is that we should never ever have a situation in which one catastrophic failure of some component of the airplane causes us to lose the airplane. These backups to the backup backing up the backups is why we can get on an airplane with almost 100% assurance that we're going to get where we want to go safely. This philosophy requires multiple redundant systems to prevent single-point failures.

In high-risk engineering, rigidity is fragile. If a system has only one way to function, it is doomed to fail eventually. Aviation is the safest mode of transportation not because its engines are perfect, but because engineers design assuming failure is inevitable. The APU represents the 'backup of the backup' - accepting vulnerability and providing multiple layers of protection. The small hum from the tail is the sound of engineering security working for passengers.

The Voyage includes redundant systems: dual trains, dual restraints (lap bar and seat belt), multi-block safety zones, passive mechanical backups like the anti-rollback, sensor-based interlocks, emergency access platforms, and valleys and hills. The ride doesn't rely on just one thing going right—it's built so many things have to go wrong before there's ever any chance of a risk. This philosophy of multiple independent safety layers ensures that a single point of failure cannot result in an accident, embodying the engineering principle that safety is engineered through redundancy rather than single-point solutions.

The Shinkansen applied the principle of 'intrinsic safety' - designing systems so that hazards cannot occur rather than adding protective measures. Rather than designing better brakes to stop trains in emergencies, they designed closed-loop systems with no grade crossings, fully protected tracks, and no way for people or vehicles to enter the right-of-way. This eliminates the root cause of accidents rather than managing symptoms. Additionally, they built redundancy - each train car has its own engine, so if one fails, the train continues moving. This 'graceful degradation' principle (where systems fail gradually rather than catastrophically) is now standard in aviation and data center design. The Shinkansen team intuitively understood these principles decades before they were formally articulated.

Fail-safe design is an engineering principle where systems are designed to fail in ways that protect users rather than cause harm. Railroad crossings exemplify this: when any component fails (broken wire, dead battery, flooded joint), the system defaults to a safe state—red lights, gates down, bells ringing. Engineers arrange components so failure produces a red light, not a green one. The only way to defeat such a system is to lie to it, not break it. This philosophy, developed by engineers who assumed everything would eventually break, makes railroad crossings one of the safest heavy transport systems ever built.

Elevator safety is governed by international standards including ISO 36811 (Mercosur), EN 81 (European standard), and ASME A17.1 (American standard). These standards are continuously updated to incorporate new technologies and safety concepts. The ISO 8000 series aims to unify these different regional standards into a single comprehensive framework, expected for release around 2025. Compliance with these evolving regulations requires retrofitting existing elevators to meet modern safety requirements.

Currently, two organizations are certified by ANSI to accredit elevator inspectors: the Elevator Industry Preservation Fund (through the International Union of Elevator Constructors) and NAIA (National Association of Elevator Safety Authorities International). Both must follow QI1 requirements including 10 continuing education hours annually, original examination, and possession of all necessary code books. ASME develops A17.1, one of the oldest and most respected technical standards in the United States, comparable to the National Electrical Code. ASME serves as the parent organization that develops foundational elevator standards while A77 handles specific technical standards for technicians, representing a vertical integration of elevator technology standards.

ASME A17.1 is the safety code for elevators and escalators, written for commercial buildings. Key requirements include: power requirements (often three-phase power), structural requirements (escalators weigh tons and need reinforced pits and heavy-duty support), weatherproofing (outdoor installation requires specialized components, drainage, and heating elements), and safety features (sensors, emergency stops, skirt guards, comb plates). The code assumes indoor commercial environments, not suburban residential porches.

Las normas principales son ISO 4344 (europeas) y ASME A17.6 (americanas). Los criterios de descarte incluyen: reducción de diámetro (más del 6%), rotura de alambres (más de 15 alambres por paso en condiciones normales, más de 30 en condiciones de rus), corrosión visible, desgaste localizado, y alargamiento excesivo. La norma ASME A17.1 establece reglas de seguridad con factores mínimos de relación de sobre y factores de servicio.

Elevator codes and standards are established by ANSI/ASME A17.1 (American National Standard Safety Code for elevators, dumbwaiters, escalators, and moving walks) and local building codes. Standard sizes and shapes are determined by the National Elevator Industries Incorporation (NEII). Recommended capacity and design for passenger elevators vary by occupancy type. Type and design speeds for elevators are compared in standard tables. Recommended performance includes specific loading capacities for both passenger and freight elevators. Low-rise group elevators should serve the lower portion of the building while high-rise group elevators travel directly from the main stop to upper portions.

Modern predictive maintenance relies on sophisticated technical infrastructure spanning sensor deployment, cloud processing, and machine learning. The Lift Manager system demonstrates this through three sensor units: a main unit containing eight integrated sensors (accelerometer, gyroscope, magnetometer, humidity, pressure, temperature, acoustics, and light sensors), a door sensor using three-axis accelerometers and magnetometers, and a laser range finder for floor leveling accuracy. These sensors continuously collect operational data that feeds into Microsoft Azure cloud infrastructure for AI analytics. The system creates digital twins of individual elevators using 80 years of industry expertise and over 300,000 annual inspections. Algorithms are tuned to avoid false positives from normal brand-specific behaviors. Audio sensors detect acoustic signatures to identify emergency situations like man-trap conditions. This technical foundation enables anomaly detection and predictive component failure analysis through continuous performance trending.

Mitsubishi Elevator Europe implemented a predictive maintenance solution using IoT technology and mobile applications, which enabled remote elevator control, real-time issue updates for employees, and enhanced R&D insights, resulting in improved operational efficiency, reduced downtime, and better alignment between business objectives and environmental sustainability goals.

Otis Elevator Company demonstrates how IoT technology and data analytics enable predictive maintenance in elevator systems by collecting performance data from edge devices installed on elevators, analyzing this data to predict equipment failures before they occur, and using these insights to optimize maintenance schedules, reduce downtime, and improve customer satisfaction. The company collects data from controllers, drives, and door performance sensors, aggregates it through edge computing devices, and processes it in a cloud-based data lake to generate actionable insights for four key personas: external customers, call center agents, remote experts, and field technicians. This digital transformation strategy enables Otis to drive service growth, increase pricing, and build customer loyalty while making their elevators more competitive against independent service providers.

Long-range wireless industrial IoT sensors enable predictive maintenance by monitoring equipment health through vibration, temperature, and current measurements, with data transmitted via encrypted mesh networks to edge computers that process information and send it to cloud platforms for analysis and alerting.

IoT success requires a holistic transformation of business strategy, leadership commitment, organizational change management, talent development, process redesign, and partnership strategy, rather than focusing solely on technology implementation; companies must adopt portfolio approaches with quick wins and big bets, involve business teams early, communicate changes proactively, and address challenges early in the implementation cycle to achieve meaningful value creation beyond traditional predictive maintenance use cases.