In general, the processing time, the processing costs and the processing quality are considered as production performance indicators for integrated process planning and shop scheduling problem. However, the environmental impact such as energy consumption is not taken into account completely. In this paper, a mathematical model for process planning and shop scheduling is established for optimizing completion time and energy consumption by changing the weighting factors. An improved hybrid simulated annealing and genetic algorithm is adopted to solve the problem, which is based on the strength of global search for genetic algorithm and local search for simulated annealing. Finally, a case study is given. The experimental result shows that the approach is feasible and efficient.