Step 9 Mission Concept Selection

This section is concerned not with the detailed engineering decisions for a space mission, but with the broad trades involved in defining the overall mission—whether to proceed with it and what concept to use. Decisions for space missions fall into three broad categories: (1) go/no-go decision on proceeding with the mission; (2) selection of the mission concept; and (3) detailed engineering decisions, which are generally described throughout this book.

In principle, the go/no-go decision depends on only a few factors, the most important of which are:

• Does the proposed system meet the overall mission objectives?

• Is it technically feasible?

• Is the level of risk acceptable?

• Are the schedule and budget within the established constraints?

• Do preliminary results show this option to be better than nonspace solutions?

In addition to the above technical issues, a number of nontechnical criteria are ordinarily equally or more important in the decision-making process:

• Does the mission meet the political objectives?

• Are the organizational responsibilities acceptable to all of the organizations involved in the decision?

• Does the mission support the infrastructure in place or contemplated?

For example, a mission may be approved to keep an organization in business, or it may be delayed or suspended if it requires creating an infrastructure perceived as not needed in the long term. The mission analysis activity must include nontechnical factors associated with space missions and see that they are appropriately addressed.

The top-level trades in concept selection are usually not fully quantitative, and we should not force them to be. The purpose of the trade studies and utility analysis is to make the decisions as informed as possible. We wish to add quantitative information to the decisions, not quantify the decision making. In other words, we should not undervalue the decision-maker's judgment by attempting to replace it with a simplistic formula or rule.

Table 3-10 shows how we might try to quantify a decision. Assume that a system costs $500 million, but an improvement could save up to $300 million. To save this money, we could use option A, B, or C. Option A would cost $35 million, but the probability of success is only 70%; B would cost $100 million with 99% probability of success; C would cost $200 million with a 99.9% probability of success.

TABLE 3-10. Mathematical Model of Hypothetical Decision Process (costs In $M). Numerically, we would choose B or K if it were available. Realistically, any of the choices may be best depending on the decision criteria.

Current Cost

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