## 1 Introduction  
Product innovation improves our living environment and enables high-tech developments. Yet, linear product design has led to critical environmental impacts, which, in turn, have remarkably affected the safety of property and life. This is best reflected by the increasingly frequent and intense extreme weather events. Hence, environmentally friendly eco-designs are becoming increasingly popular. They aim to alleviate environmental impacts and enhance the benefits to the entire ecosystem. Eco-designs consider both product functions and the effects of their life cycles on the environment. In order to minimize the environmental impacts due to processing, [PERSON] et al. [1] combined computer-aided design (CAD) and life-cycle assessment (LCA) to estimate the environmental impacts of a sample part caused by different processing procedures. In this way, the procedures with the least environmental impacts could be selected. Meanwhile, [PERSON] et al. [2] adopted energy-based life-cycle assessment (Em-LCA) to the use of laser additive manufacturing and that of computer numerical control (CNC) machining for processing AISI 4140 spur gears and propose sustainable manufacturing strategies. For product assembly, [PERSON] et al. [3] used LCA to verify that the introduction of the design for assembly (DFA) method for an electronic safety product could reduce the environmental impacts. Similarly, for product recycling, [PERSON] et al. [4] chose a portable cassette and CD player for possessing signs that included information at the product obsolescence stage during design. They utilized EeoLCI assessments to reduce the environmental impacts of the recycling processes. In addition, LCA can be used to compare products in the same category. [PERSON] [5] and [PERSON] et al. [6] performed LCAs to determine the environmental impacts of a field emission display (FED) television. By integrating LCA and optimization, an optimized design that considers the environmental impacts can be obtained. [PERSON] et al. [7] combined LCA and ant colony optimization to enhance the green decision-making efficiency of an oven during product design. [PERSON] and [PERSON] [8] applied the response surface method (RSM) and Design Expert to develop eco-efficient concrete. [PERSON] et al. [9] established a life-cycle simulation (LCS) model for an EV battery pack to give design schemes with the smallest environmental loads. In the meantime, [PERSON] et al. [10] adopted CAD, LCA, and life-cycle inventory (LCI) in three different machine rod backets to identify the processing scheme with the least waste generated. [PERSON] et al. [11] combined LCA and artificial neural network (ANN) models to predict the green chemicals that could be used as alternatives. [PERSON] et al. [12] used RSM and the neural network method to obtain the optimal energy efficiency of shell-and-tube heat exchangers during their production. With the help of the RSM and genetic algorithm (GA), [PERSON] et al. [13] achieved the green goals of nanofluid MQL micro-drilling processing. [PERSON] [14] utilized the Taguchi method to identify the additive manufacturing process parameters that meet the sustainability requirements. [PERSON] and [PERSON] [15] performed response surface analyses to find the optimal value of surface roughness on 17-4 precipitated hardened stainless steel (PH SS) material to achieve the longest service lives for the processing tools. In another study [16], these two authors employed the Taguchi method to obtain the maximum number of processing times for special stainless steel materials to achieve the longest service lives for the processing tools. From the aforementioned literature, it is clear that optimization can, at the design stage, effectively reduce the consequential environmental impacts. Although enhancing the eco-efficiency is one of the emphases of eco-design, this target should be aligned with other existing design goals, such as those related to the production cost, mechanical properties, and material selection.