Maintenance and in particular the repair in terms of actual physical activities that are required to reproduce the
state of a machine can be seen as part of the integral logistics management [1]. Tasks like dispatching the orders and
the related allocation of resources of personnel and equipment have to, in general, be fulfilled in a similar way as
production environments. General inspection and maintenance as well as repair activities include resource allocation
of working places and maintenance teams for queued orders. This assignment problem is referred to as a so-called
“scheduling” [2] and is part of planning and control. The logistical process chain of maintenance order processing
thus integrates personnel and team planning, equipment and material logistics as well as spare parts logistics. The
concrete design of these processes is highly dependent on the chosen maintenance strategy [3].
Especially when pursuing a condition-based strategy, the effective integration of state information in the planning
and control level is critical for the further processes [4]. A long-term maintenance planning is replaced by a medium
time planning which allows relatively good state forecasts of the components and, in conclusion, a good scheduling
of appropriate maintenance or repairs. However, faults which lead to a sudden failure must be scheduled as urgent
jobs and initialize a rescheduling [3]. The challenge is to find an effective approach to handle the complex situation
for the operational maintenance processes as well as the spare part logistics. A central information processing,
planning and control system for this problem would require extensive information for each subsystem. Nevertheless,
uncertain estimates cause a lack of planning reliability [5]. However, heterarchically organized objects, which
follow their objectives through decentralized self- control, promise better efficiency for the overall system [6]. The
general suitability of autonomous and decentralized decision-making systems for logistics planning and control
processes for specific scenarios have been demonstrated already [7, 8, 9]. For spare parts logistics and maintenance
processes this has not been fully investigated yet. However, condition monitoring systems and assessment methods
would allow logistical objects to independently know their condition. As a result, they can be used for local
decision-making and further activities, which is a precondition for autonomous structures. The planning and control
by corresponding objects which negotiate the best possible behavior independently via multi-agent systems is one
example. It is put onto the shortlist of suitable methods in preactive maintenance concepts [10, 11].
In the following, the paper gives a valuable insight into a modernized approach of preacting maintenance concepts
through autonomous and decentralized decision-making systems with today’s opportunities and tomorrow’s
challenges. In chapter 2, a literature review that analyzes today’s state of the art is performed, followed by a methodological
description of the preacting concept in chapter 3. In addition, some cases will be shown and discussed to
investigate the practical eligibility following the technical approach of the concept in chapter 4. Chapter 5 gives a
final conclusion and an outlook for further development and research requirements.