Coordination plays a key role in solving decomposed optimal system design problems. Several coordination strategies have been proposed in the multidisciplinary optimization (MDO) literature. They are usually presented as a sequence of statements: the parallel nature of the multidisciplinary subproblems is often either not addressed or only briefly mentioned. However, a more formal description of the concurrency in the coordination is essential, in particular for large and non-hierarchic coordination architectures. This paper proposes to use concepts from communicating sequential processes (CSPs) developed in concurrency theory. CSPs allow the description of the MDO coordination as a number of parallel processes that operate independently and communicate with each other synchronously over pre-defined channels. For this purpose, we introduce elements of the language chi, a CSP-based language that contains data types such as reals, arrays, lists and tuples. The accompanying software tool set that enables the execution of a chi specification has been extended with a Python interface so that function calls to external software can be carried out. Through this interface, chi has been coupled with Matlab to run coordination specifications of distributed optimal system design problems on single or multiple parallel computers. An optimal design example is used to illustrate this. It is concluded that the use of a CSP-based language such as chi for coordinating the solution of MDO problems is quite promising