Industrial applications and processes such as quality inspections, pick and place operations, and semiconductor manufacturing require accurate positioning control for achieving the high throughput of the assembly machines. Vision-based sensing is considered to be a potential means to achieve robust positioning control which is referred to as a vision-in-the-loop (VIL) system. In such motion systems, the point-of-control and the point-of-interest are often different due to several physical factors. In this case, validation of a system is done only when a machine prototype is available. A physical prototype is often expensive and infeasible in real-life. This paper proposes an evaluation framework for VIL systems targeting a predictable multi-core embedded platform. The presented framework offers model-in-the-loop (MIL), software-in-the-loop (SIL), and processor-in-the-loop (PIL) simulation features for evaluating the closed-loop performance of industrial motion control systems. As a deployment platform, we consider a predictable embedded platform CompSOC. The predictable nature of the CompSOC platform guarantees periodic and deterministic execution of the control applications and allows verification of the timing properties and performance of the VIL system. Additionally, the framework offers automatic code generation feature targeting the CompSOC platform. Closed-loop simulation setup models the system dynamics and camera position in the CoppeliaSim physics simulation engine and simulates the system software in C and MATLAB. CoppeliaSim runs as a server and MATLAB as a client in synchronous mode. We show the effectiveness of our framework using a vision-based motion control example.