Design for manufacturability (also sometimes known as design for manufacturing or DFM) is the general engineering practice of designing products in such a way that they are easy to manufacture. The concept exists in almost all engineering disciplines, but the implementation differs widely depending on the manufacturing technology. DFM describes the process of designing or engineering a product in order to facilitate the manufacturing process in order to reduce its manufacturing costs. DFM will allow potential problems to be fixed in the design phase which is the least expensive place to address them. Other factors may affect the manufacturability such as the type of raw material, the form of the raw material, dimensional tolerances, and secondary processing such as finishing.
Depending on various types of manufacturing processes there are set guidelines for DFM practices. These DFM guidelines help to precisely define various tolerances, rules and common manufacturing checks related to DFM.
While DFM is applicable to the design process, a similar concept called DFSS (design for Six Sigma) is also practiced in many organizations.
For printed circuit boards (PCB)
In the PCB design process, DFM leads to a set of design guidelines that attempt to ensure manufacturability. By doing so, probable production problems may be addressed during the design stage.
Ideally, DFM guidelines take into account the processes and capabilities of the manufacturing industry. Therefore, DFM is constantly evolving.
As manufacturing companies evolve and automate more and more stages of the processes, these processes tend to become cheaper. DFM is usually used to reduce these costs. For example, if a process may be done automatically by machines (i.e. SMT component placement and soldering), such process is likely to be cheaper than doing so by hand.
For integrated circuits (IC) Achieving high-yielding designs, in the state of the art VLSI technology has become an extremely challenging task due to the miniaturization as well as the complexity of leading-edge products. Here, the DFM methodology includes a set of techniques to modify the design of integrated circuits (IC) in order to make them more manufacturable, i.e., to improve their functional yield, parametric yield, or their reliability.
Background
Traditionally, in the pre-nanometer era, DFM consisted of a set of different methodologies trying to enforce some soft (recommended) design rules regarding the shapes and polygons of the physical layout of an integrated circuit. These DFM methodologies worked primarily at the full chip level. Additionally, worst-case simulations at different levels of abstraction were applied to minimize the impact of process variations on performance and other types of parametric yield loss. All these different types of worst-case simulations were essentially based on a base set of worst-case (or corner) SPICE device parameter files that were intended to represent the variability of transistor performance over the full range of variation in a fabrication process. Additionally, SPICE models should have mismatches built into them for analog circuit simulations. Many mismatches are size and orientation dependent, which can be well modeled. Always "copy exactly" when doing analog layouts as many mismatches are not well understood or controlled (i.e. if one device has North to South current flow, all matched devices should have North to South current flow).
Taxonomy of yield loss mechanisms
The most important yield loss models (YLMs) for VLSI ICs can be classified into several categories based on their nature. Functional yield loss is still the dominant factor and is caused by mechanisms such as misprocessing (e.g., equipment-related problems), systematic effects such as printability or planarization problems, and purely random defects. High-performance products may exhibit parametric design marginalities caused by either process fluctuations or environmental factors (such as supply voltage or temperature). The test-related yield losses, which are caused by incorrect testing, can also play a significant role.