Fire Department Action Patterns for IT Support?

The aim of a maintenance organization is to ensure long-term, efficient and disturbance-free operation throughout the entire lifespan of the ERP system [1]. Maintenance organization includes the processes of IT service management, training, project management as well as internal communications and documentation. The focus here is on the service processes involved in ERP operation, such as those mapped in the ITIL process model (IT Infrastructure Library), and the processes for employee training on IT issues. Training in this sense includes all activities that serve to maintain, expand and adapt professional knowledge, skills and abilities [2].

Negative consequences of non-optimal maintenance organization can include unforeseen support costs and time spent manually compen­sating for inadequate data quality. Maintenance organization deals with unforeseen incidents whose volume and severity cannot be predicted in advance. Figure 1 shows the distribution of incidents across five different difficulty levels over an 80-day period in the organization examined in the scope of this article.

Patterns of action in emergency organizations

An emergency organization is an organization whose purpose is to provide aid in urgent situations to maintain or restore the regular lifestyle of a given person or community [3]. The service provided by emergency organizations and the troubleshooting undertaken in the IT area are similar, both in terms of the urgency of action and objective as well as in terms of structure and prevailing framework conditions (see Fig. 2).

The core competence of emergency organizations (such as rescue, fire brigade, police, technical relief organizations or military) is – in a figurative sense – the elimination of “disturbances” through operations of various kinds.

These organizations have specific structural properties in place in order to successfully manage their operations and patterns of action. Structural characteristics of emergency response organizations include, for example, an operational organization pattern that differs based on type of damage, the presence of self-similar structural elements and a clearly defined allocation of roles that ensures that tasks are carried out as smoothly as possible, even when the personnel composition of a response team changes.

Action patterns are procedures that are applied at different organizational levels to achieve a specific goal [5]. These include, for example: situational investigation methods, specific management procedures and the development or orchestration of predefined, often event-specific standards (e.g. a one-room fire is handled differently than a major fire) [6].

The action patterns shown in Figure 3 were recommended for testing in an IT context.

For this purpose, a workshop was held with those responsible for the maintenance organization and an expert for emergency organizations. Our experiment was designed to examine whether transferring the action patterns used by emergency organizations to the context of an IT maintenance organization makes sense and enables improvements within the latter.

These patterns of action can be explained as follows: Standards can help emergency services prepare for and carry out a specific type of operation by providing workforce guidance (e.g. guidelines for dividing tasks at the operation site, documents or checklists, standardized terminology, description of the tasks handled by a specific role). Emergency organizations anticipate the expected resource requirements for certain types of operations in advance. These are determined by the alert keyword and the emergency location.

There are detailed plans for certain places and objects that enable the emergency services to quickly orientate themselves at the scene and thus shorten the time required to investigate the location. Among other things, these detailed plans may show the individual levels of a building, list sources of danger and predefine appropriate buffer zones for resources.

Material and human resources are transferred into ready-to-use, modular and combinable units in order to improve the ability to react when damage occurs. The emergency services undergo training in which they are provided with basic and role-specific knowledge.

In simulations or large-scale exercises, emergency services practice the application of the operational standards at regular intervals – sometimes on a mandatory basis.

In a short training course, the employees of the IT maintenance organization were made familiar with the general operating patterns followed by emergency service organizations. The time between receipt and closing of the ticket was used as an evaluation parameter for the experiment. This data was relatively easy to collect because a ticket management system was in place. The tickets were divided into five levels of difficulty, ranging from very simple to solve to extremely difficult.

The classification is based on an assessment of the tickets made by the employees of the IT maintenance organization. In order to make the workload of the maintenance organization during this time comparable for the experiment, the levels of difficulty were assigned minute values, resulting in an overall workload value of 4,372.5 minutes in the first evaluation period. The opening times for tickets vary depending on the difficulty of the incident. The individual categories are not thus comparable with each other.

On the one hand, this is because serious and very serious incidents only occur very rarely, and on the other hand, it is due to the way tickets are assigned to team members. Tickets also arrive at random times and are thus not subject to any semblance of regularity.

This also makes it very difficult to ensure consistent staff utilization in the IT support organization.

Applying emergency action patterns to the IT support field

This experiment examined whether training IT employees in the action patterns of emergency organizations had a positive impact on IT support work. The time period of the experiment is shown in Figure 6. In the post-training phase of the experiment, a workload value of 5,295 minutes was recorded, which constitutes an increase of approximately 21% compared to the pre-training phase.

In most of the categories considered, not enough data accrued during the respective study periods to be able to make statistically relevant statements about changes to the time a ticket was open. However, clear differences can be seen in the “moderately difficult” category.

Despite an approximately 20% higher ticket workload, by applying the action patterns of emergency organizations, a noticeable reduction in time open for tickets of moderate difficulty was achieved. In the authors’ opinion, the incorporation of certain patterns of action employed by emergency organizations is certainly justified for IT maintenance organizations.

The action patterns used in the experiment were subjected to an evaluation by IT support employees.

Two of the six action patterns suggested for use in IT support were viewed as particularly suitable (see Fig. 8). In addition to the unsurprising support for staff training, the advance planning of resource requirements was of particular value, as was the creation of ready-to-use, modular and combinable units. Some of the more specific patterns of action, such as pre-planning for locations, were deemed less useful by IT support staff.

Evaluation of the approach

In order to avoid excessive intervention in the already heavily stressful working atmosphere of the IT maintenance organization, no more intensive intervention beyond the training was carried out during the two-phase investigation. This leaves questions unanswered, e.g. such as which action patterns are used in which specific cases. Nevertheless, it seems extremely useful to familiarize IT maintenance organizations with the patterns of action employed by emergency organizations. To ensure that these patterns of action are indeed applicable, an appropriate method kit that describes suitable patterns of action and their possible applications should be developed. However, further experiments are necessary to make this a reality.

You might also be interested in

Experiential Knowledge Powered by AI  Practical insights from industry Martin Schmauder , Gritt Ott , Bianca Windisch

The use of experiential knowledge is a key success factor for companies. Based on four corporate case studies, this article analyzes the technical, organizational, and personnel challenges associated with the use of retrieval-augmented generation (RAG) systems. The results show that the success of such systems depends on the strategic development and maintenance of the knowledge base, as well as on employee engagement.

Industry 4.0 Science | Volume 42 | 2026 | Edition 5 | Pages 128-135 | DOI 10.30844/I4SE.26.5.15

Inclusive Work System Design Automation, standardization, and adaptability Sebastian Schlund

The design of inclusive work systems is gaining importance due to demographic change and the increasing digital penetration of value creation processes. While traditional ergonomic approaches are based primarily on percentile logic and thus address only a portion of the user population, the integration of digital technologies opens up new possibilities for the dynamic and individualized adaptation of work systems. This article presents a conceptual framework for inclusive work system design that integrates standardization, automation, and adaptability. Methodologically, the article is based on a conceptual analysis of existing approaches from ergonomics and human-centered design. The article makes a theoretical contribution to the systematization of inclusive work system design and identifies areas of focus for further research and industrial practice.

Industry 4.0 Science | Volume 42 | 2026 | Edition 5 | Pages 70-76 | DOI 10.30844/I4SE.26.5.8

MTM Analyses with AI and Rule-Based Algorithms An approach to interpreting textual process descriptions Constantin Eckart , Martin Benter, Peter Kuhlang

MTM methods are a proven standard for analyzing and designing human work processes. However, work planners continue to face challenges in applying these methods correctly and efficiently. Artificial intelligence — particularly in the case of large language models — holds significant potential for combatting these challenges. However, the use of AI raises legitimate questions regarding the reliability and traceability of the results. The approach presented here combines LLMs with a rule-based algorithm to extract the information required for MTM analyses from textual process descriptions such as work instructions. This information is then translated into MTM analyses in accordance with the MTM methodology. This approach ensures that the resulting analyses can be transparently traced back to the original input data by the user.

Industry 4.0 Science | Volume 42 | 2026 | Edition 5 | Pages 62-69 | DOI 10.30844/I4SE.26.5.7

AI-Powered Lubrication Strategies for Thread Forming Adaptive spray jet control to increase process reliability and tool life Reinhard Schmied, Marco Susic, Christian Donhauser

Thread forming requires precise lubricant application because high contact pressures and process temperatures strongly influence tool loading, friction, and process stability. Although minimum quantity lubrication (MQL) systems are widely used, current spray-based approaches can still suffer from spray losses, insufficient wetting of the thread grooves, and unstable droplet transport. This article presents a concept for adaptive precision lubrication in thread forming based on computational fluid dynamics (CFD)-supported flow analysis, experimental validation, and artificial intelligence (AI)-assisted optimization. The focus is on droplet size, spray jet geometry, nozzle position, ambient flow conditions, and their influence on wetting intensity. Preliminary simulation-based investigations indicate that data-driven optimization can help identify wetting deficiencies and support the development of future control strategies for resource-efficient lubricant application.

Industry 4.0 Science | Volume 42 | 2027 | Edition 3 | Pages 76-83

Optimized Manual Processes in Automotive Production A module-based approach for the efficient creation of work system simulations Barbara Brockmann, Tobias Jurk, Beate Stoffels, Jochen Deuse

In the manufacturing industry, the integration of digital human models into the product development and manufacturing process is becoming increasingly important. Particularly in assembly, which is characterized by a high proportion of manual tasks, motion simulations enable a realistic representation of human work and thus make a significant contribution to the evaluation of motion economy, process validation, and efficiency improvement. However, widespread application in production planning faces various challenges, such as the high initial effort required to create human simulations as well as volatile planning conditions. This article presents a practice-oriented solution from the automotive assembly sector that enables the creation of simulations with reduced effort as well as their early and consistent use in the planning process.

Industry 4.0 Science | Volume 42 | 2026 | Edition 3 | Pages 48-55

SmartBending—Inline Measurement for Process Correction Inline process optimization for error compensation in swivel bending Christian Donhauser , Reinhard Schmied, Marco Susic

Swivel bending is an established forming process that minimizes material loss and enables efficient use of resources. However, the process requires complex optimizations that have traditionally relied heavily on the expertise of machine operators. This results in significant time and material costs, as optimization steps are performed iteratively. Given the shortage of skilled workers, a technological upgrade of the machines in line with Industry 4.0 is necessary. As part of a research project, intelligent sensor technology was used to record critical influencing factors that reveal correlations between product defects and machine deformations. Based on this, a methodology was developed that forms the foundation for inline compensation, enabling the equipment to autonomously adjust process parameters to correct product defects and, in the long term, enable defect-free production from the very first component.

Industry 4.0 Science | Volume 42 | 2026 | Edition 3 | Pages 134-141