An automatable, robust, high-performance online multidimensional liquid chromatography (MDLC) platform comprising of pH 10 reversed-phase (RP), strong cation exchange (SCX), and pH 2 RP separation stages has been integrated into a modified commercial off-the-shelf LC instrument with a simple rewiring, enabling accelerated routine qualitative and quantitative proteomics analyses. This system has been redesigned with a dual-trap column configuration to improve the throughput by greatly decreasing the system idle time. The performance of this new design has been benchmarked through analysis of the total lysate of S. cerevisiae, in comparison with that of the former tailor-made system featuring more complicated components; the total run time per “load-and-go” LC/MS analysis was approximately 24 h, with minimal idle time and no labor-intensive steps. This platform features high-resolution fractionations, ease of use and a high degree of user programmability in the first two chromatographic dimensions, allowing flexible and effective sampling with (RP–SCX–RP) or without (RP–RP) the inclusion of SCX sub-fractionation; good proteome coverage and reproducibility was demonstrated through the analyses of bacterial, cell culture, and monkey brain tissue proteomes. The viability of the 3D RP–SCX–RP has been proven in proteome-wide studies of STO fibroblasts and yeast tryptic digests, resulting in extended proteome and protein coverages with high reproducibility—in particular, discovering extra-hydrophilic peptides—at the expense of the acquisition time. The identified inventory of the rat pheochromocytoma PC12 cell proteome—a total of 6345 proteins and 97 309 unique peptides is the most comprehensive dataset to date—provides an example of the value of the 3D RP–SCX–RP. The use of orthogonal chromatographic dimensions in the 3D RP–SCX–RP also circumvents the issues of isobaric interference of mass-tagging background contaminations, while significantly improving the accuracy of isobaric tags for relative and absolute quantitation (iTRAQ)-based protein quantitation experiments.