Optimum-AIV, A Planning Tool for Spacecraft AIV

Optimum-AIV, A Planning Tool for Spacecraft AIV Authors: Y.Parrod, Matra-Marconi Space (F) and S.Valera, Simulation and Electrical Facilities Division, ESTEC

Contractors: CRI (DK), Matra-Marconi (F), AIAI (UK)

Funding: ESTEC Basic Technology Research Programme


Planning is a key issue in the management of the assembly, integration and verification (AIV) activities of a space project. Not only technical achievements are important for the success of a project; cost and planning aspects are also important. As many participants (agencies, contractors, launcher authorities, users) and costly facilities are involved in the fulfillment of a project, a delay caused by one of the participants normally leads to serious problems for the others.

At all levels of a space project, managers are concerned with planning, and to this end, they control closely the progress of the work; however it is difficult to find a planning tool tailored to their specific needs. General purpose commercial tools are either too simple to represent their problems correctly or else they are too complex to be used interactively.

Due to the special characteristics of space projects (mainly their size and duration), well adapted computerised planning and scheduling systems are needed, and software tools are also needed to help solve some of the problems arising when AIV plans, initially managed by one team, are taken over by another team during the life of the project. Planning tools should be able to keep track of planning decisions and to explain the rationale of the plan, which governs the links between activities. Planning tools should also support, correctly and easily, the management of the specific constraints and solutions which are typical of AIV activities, for instance changing from single-shift to double-shift working in order to meet a deadline.

Frequently, because of the inadequacy of conventional planning tools, planning is simplified to a network problem of seeking the critical path, in which only temporal constraints are managed. To avoid managing other resources, the plan is over constrained by adding hard-precedence-links between activities. Parallel activities are rescheduled as sequential activities and alternatives which potentially existed in the process are lost. Good planning tools should be efficient enough to discourage such bad practices.

Optimum AIV

The object of Optimum-AIV is to meet specific planning requirements of AIV activities and to demonstrate the capabilities of artificial intelligence techniques to solve the problems which arise in AIV planning. Optimum-AIV is a tool designed to provide AIV team leaders with straightforward access to planning management techniques.

Optimum-AIV covers all of the basic scheduling functions. It can, for instance, define an `activities network' associate minimum and maximum delay constraints between activities, allocate shared or consumable resources to activities, and compute a schedule which meets these temporal and other resource constraints. In addition, Optimum-AIV provides some advanced planning and scheduling functions.

Structured Management of Projects

The structure of large projects can be broken down into a tree of hierarchical activities in which macro-activities are split into sub-activities. Temporal, resource and precedence constraints are propagated through this hierarchical structure. It is, for instance, possible to allocate resources not only during the execution of an activity, but also between concurrent activities.

Process Modelling

Activities can be modelled as operators containing preconditions and effects. Let us suppose that the outcome of an integration activity may be expressed as `equipment A integrated on Platform'. Preconditions must be met before the activity can start, and the activity produces effects which change the process configuration. Optimum-AIV checks the preconditions for an activity using the current process configuration, and computes the new process configuration from the effects of that activity.

This feature allows one to specify explicitly the logic which lies behind precedence links, and to check automatically the logical consistency of the plan.

Scheduling features

Optimum-AIV offers a resource-driven scheduling mechanism to facilitate the specification of different scenarios for working hours, which can be easily modified to observe the direct impact on the duration of the activity to which those resources have been allocated. The working hours can also be dependent on the activity to which they are allocated. For instance, double-shift working can be restricted to a single work package on which additional effort is needed.

Optimum-AIV also has an automatic mode to compute the schedule and to resolve conflicts of demand for resources. If a conflict is detected, activities affected by the conflicts are shifted along the time axis according to the scheduling strategies defined for those activities by the user. An important point is that the development of a solution can be monitored while alternately using automatic mode and manual mode. When the schedule computed by the system in automatic mode does not correspond to the user's wishes, he may restart the scheduling process in manual mode at the scheduling point where the automatic solution diverges from the desired solution.

Global constraints

Starting with global constraints, it is possible to define constraints on activities, which are dependent on the characteristics of other activities. The syntax of global constraints follows the production rule: `IF conditions THEN conclusions'.

The conditions involve planning `objects' such as activities and/or resources. The conclusions state facts or temporal relations between activities. Using the conditions as variables, it is possible to determine relations or constraints between sets of activities which share the same characteristics. For example:

IF activity A is of type TEST of an element E and activity B is of 
     type MECHANICAL INTEGRATION of an element E
THEN activity B must be performed before activity A.

The global constraints are applied after completion of the scheduling process, in which the period allocated to each activity is computed.

Assistance in resolving conflicts

Optimum-AIV notes the various conflicts of demand for resources than cannot be solved automatically during the planning and scheduling process and supports the user in solving them.

Monitoring and Re-Planning

Optimum-AIV also provides facilities for monitoring the execution of the plan and for implementing any consequential changes in the planning which may be necessary. Last but not least, these planning functions are supported by a clear and user-friendly man-machine interface which facilitates access to information.


Optimum-AIV is now used by Matra-Marconi Space for planning the production of the vehicle equipment bays (VEB) for the Ariane-4 launcher. Here, scheduling is characterised by the fact that, at a given time, several VEBs may be concurrently in production and competing for available resources of manpower and materials.

The main criteria which have led the Ariane-4 project management to the choice of this planning tool are the following:

A module for automatically allocating available equipment amongst VEBs has been developed and works in conjunction with the scheduling module based on Optimum-AIV.


Optimum-AIV provides unique features for the presentation and editing of AIV planning and scheduling information. This information is used to check the logic of the planning and to specify global constraints on the project.

Optimum-AIV can also model a large set of scheduling constraints, and it provides the facilities to manage and solve problems within these constraints. It is thus possible to achieve an exact representation of the constraints acting on a project and to get a more reliable project schedule.

Optimum-AIV is now in use on pilot projects at ESA and also at Matra-Marconi Space. The objective of these projects is to obtain feedback from user experience in applying the tool to practical problems, with a view to optimising it for planning AIV activities in an operational environment.