Drones and Robots in Inspection: Checking Plant Without Downtime

Drones and robots inspect plant without downtime when the inspection has so far required scaffolding, rope access or a shutdown and a sensor can capture the damage you are looking for. The economics come mainly from avoided downtime days and less from the price of the inspection itself. Whether deployment pays for your assets is answered by a cost model with five items, and whether it takes hold in the inspection routine is decided by the organisation.

This article is written for operators of industrial plant and energy networks who are responsible for recurring inspections. It compares the technology by field of use, works through a business case with an example and describes how a pilot reaches the regular inspection plan. Legal questions about drone operation and inspection duties are a matter for specialist lawyers and the competent authorities. This article provides an overview and does not constitute legal advice.

When do drones and robots pay off in plant inspection?

Drones and robots pay off when access to the inspection point costs more than the inspection itself. This applies to chimneys, boilers, tanks, wind turbines, high-voltage pylons, the roofs of large halls and pipe bridges. In these cases scaffolding, rope-access teams, aerial work platforms, the emptying and gas-freeing of vessels or the shutdown of the plant cause the bulk of the cost. A robot that delivers the same finding without anyone having to climb and without production stopping changes that calculation.

The picture differs for plant that stands still on schedule anyway and is easy to reach. There the robot replaces an inspection with little access cost, and the business case works only through more frequent measurement or better data. As a rule of thumb for pre-selection, where access effort makes up more than half of the total cost of an inspection, the calculation pays off, and below that it seldom does. The threshold is this article's own judgement and not a standard figure, and the calculation below lets you check it for each asset.

Which technology suits which inspection task?

There are four device groups with different strengths, and the inspection task determines the choice. Aerial vehicles carrying a camera, thermal imager or laser scanner capture large, hard-to-reach exterior surfaces quickly and suit facades and roofs as well as rotor blades, overhead lines or chimneys. Their limits are wind, flight times of typically under an hour per battery and tight spaces with obstacles. For the interior of vessels or boilers there are collision-tolerant aerial vehicles that fly in confined spaces without GPS.

Crawler robots with magnetic wheels move along the steel walls of tanks or pipes and carry ultrasonic sensors for wall-thickness measurement. They deliver readings that a camera cannot reach, such as corrosion beneath the surface. Four-legged walking robots, on sale since 2020 from Boston Dynamics among others and by the Swiss company ANYbotics, patrol facilities on regular rounds and read gauges along the way. They detect heat sources or gas leaks and move over stairs and grating. For areas with an explosion hazard every device needs an appropriate approval under the European ATEX rules, which the manufacturer must evidence. Finally there are underwater vehicles for basins and dam walls.

How do you calculate the business case for inspection robots?

The business case consists of five items that you set against each other per asset and inspection cycle: the cost of downtime, the cost of access, the cost of the inspection itself, the cost of evaluation and the follow-on cost of damage that goes unnoticed. The first item is the number of downtime days multiplied by the contribution margin of one operating day. It is often the largest and is not carried in inspection budgets, because it arises in production. For exactly that reason inspection and production should draw up the calculation together with controlling.

The following example illustrates the logic of the calculation. The values are assumed and are not market data. A plant with a contribution margin of 40,000 euros per operating day is inspected every two years in a three-day shutdown. The shutdown costs 120,000 euros. Scaffolding and cleaning come to 40,000 euros and the inspectors to 10,000 euros, which makes 170,000 euros per cycle. With a robot deployed during live operation, the shutdown, the scaffolding and the cleaning fall away. What remains is a service provider or equipment cost of 30,000 euros, spot checks by specialist staff of 10,000 euros and data evaluation of 8,000 euros, a total of 48,000 euros. The saving of 122,000 euros per cycle can be set against the purchase cost or the service fee.

The fifth item is often neglected. When robot deployment makes inspection cheaper, it can be done more often, and damage is found earlier, before it forces a repair during a shutdown. This effect is hard to quantify in advance. A cautious calculation sets it at zero and treats it as a reserve.

What role does the inspector keep?

Robots extend the reach of the qualified inspector, and the judgement stays with that person. In non-destructive testing the standard DIN EN ISO 9712 governs the qualification and certification of personnel, and the assessment of a finding remains a task for these specialists. The robot delivers images and readings with position data. The inspector evaluates them and decides on the release. Work therefore shifts from climbing and measuring to evaluating and deciding, and that is a change of role with consequences for training and the inspection plan.

The greatest friction arises at the interface between departments: maintenance runs the pilot, the results go to plant management, and nobody has been given the task of evaluating them. Data volumes from flights and patrols grow quickly, and without a defined evaluation and a handover to maintenance planning, the gain stays in a folder.

How do you introduce inspection robotics into the inspection routine?

Introduction works in four steps, each ending in a decision. In the first step you select two or three assets with the highest access effort and record the baseline: the cost and duration of the last inspection and the downtime days. In the second step a pilot runs in parallel with the existing inspection, so that both methods assess the same condition. The agreement of the findings shows whether the robot detects the damage being sought. In the third step the inspection plan is adjusted, with roles for operating the device and for evaluation. The fourth step is regular operation with one metric for management, such as downtime days saved per quarter.

How such initiatives fit the question of investment and payback is shown in the article on planning robot cells. The article on human-robot collaboration is the natural complement for the effect on staff, and the question of whether renting or buying eases the start is treated in the article on robotics as a service.

Inspection robotics with Niehues Consulting

Niehues Consulting is a consultancy for AI management and organisational design from a delivery perspective, based in Düsseldorf. Founder Marin Niehues brings new technology into operations, on projects from VC-funded scale-ups to DAX 40 groups and in over 20 countries on six continents. Niehues Consulting does not supply robots and does not integrate devices. The work lies before and after: in the business case, in the requirements placed on manufacturers and service providers, in the introduction and in the roles and decision paths of the inspection routine.

The approach follows the Niehues Delivery Model. Three of its test questions matter for inspection robotics: What is the baseline, and how do we measure success? Is the business case confirmed with real values? Who is responsible for operations from day one? The entry point is a free initial consultation of 30 minutes, which you can arrange via contact. Scope and terms of an engagement are discussed there.