What is a defect in a process?

2.3.2 Porosity

Another processing defect of SLM technology is the formation of pores during the processing, which drastically reduces the mechanical properties of the part. The most important cause of pore formation is balling during the SLM process. When a large number of dispersed metal balls are formed in the melting track of the SLM, a large number of pores are present between the metal balls. Since the metal powder cannot enter the pores between the metal balls of the previous layer, when the second layer is scanned, the unfilled gap of the previous layer becomes a pore inside the SLM part. The second cause of pore formation is the introduction of pores. Since the laser-melting process is very fast, inert gas protection is often required during the processing. During the melting of the metal, a part of the gas originally distributed in the powder is solidified, as there is not enough time to overflow, so that pores are formed in the molten pool.

Assuming that particles have an average size of 45 μm, the pores in the particles automatically shrink into a spherical shape after the powder is melted. The volume of bubbles formed by equal volume is 10 μm. The Stokes formula states that the expression of the floating velocity of the gas vu is as follows:

(2.5)vu=2rg2(γl−γg)9ηl

where rg is the radius of the bubble, ηl is the viscosity of the liquid, and γl and γg are the gravity of the liquid and the gas, respectively, and the value is about equal to 10 times the density. It can be intuitively seen from the formula that the larger the volume of the bubble, the faster the floating speed. Assuming that the powder spreading thickness of each layer is 0.02 mm, the time taken for the rise can be calculated to be about 8 × 10−  5 s, and the time taken for the SLM to cool to the solid phase is about 5 × 10−  4 s. Therefore, the bubbles in the metal liquid have enough time to escape from the liquid, and it is difficult to observe macroscopic bubbles in SLM processing. For the same reason, using the solidification time and the thickness of the powder spreading, it is possible to deduce that the radius of the bubble that is too late to overflow is about 3 μm or less.

10.1 Introduction

Powder injection molding comprises several processing steps, and defects may occur in each step if care is not taken. The defects encountered could be caused by mechanical factors, such as poor mold design and mold manufacturing, or by processing related factors, such as incomplete kneading, inadequate molding pressure, injection speed, holding pressure, and non-optimized debinding and sintering parameters (Zhang et al., 1989; Hwang, 1996). Some of these defects may originate in the early processing steps but are difficult to identify because they do not manifest until after debinding or sintering. In the following section, the defects that frequently occur in each processing step are examined and their causes are explained. Hopefully, with an understanding of the scientific background of the defects, exhaustive trial and error experimentation can be avoided.

8.5.1 Introduction

The source of many packaging processing defects and reliability problems is thermal stress. In our first encounter with internal stress we saw (Section 3.3.2.2) how thermal stress could develop in a single material when constrained. Thermal stresses can also arise in so-called thermostat or bimetallic strip structures, consisting of two different materials in intimate contact. Normally it is assumed that the thermostat is unstressed at some reference temperature. Stress then develops in the thermostat as it is either cooled or heated to the use temperature because the thermal expansion coefficients of the two materials differ. A film of SiO2 on silicon is such a thermostat structure that was discussed in connection with oxidation (Section 3.3.2.4). As noted on earlier occasions, Eqn (8.1) (or Eqn (3.8)) yields the stress magnitude.

Stress can also develop in a bilayer structure by other than thermal means. Epitaxial mismatch and film-growth processes are examples of intrinsic sources of internal stress in film/substrate bilayers. The Stoney formula (Eqn (3.10)) describes the bowing of the bilayer in terms of the stress. Thermal stresses will also cause bilayers to bow. Thus, by combining Eqns (8.1) and (3.10), the predicted radius of curvature, R, of the combination is given by

(8.6)R=(1−νf)Esds26( 1−νs)dfEf[αs−αf](ΔT),

where f and s refer to film and substrate, respectively, and ΔT is the temperature difference.

The packaging structures we are about to consider differ from thermostats in that they contain three, not two, contiguous layers. Even though packaging layers are thick compared to thin films, the same principles of mechanics apply when considering response to loading. Thermal stress problems are generally complex, requiring knowledge of elasticity theory and finite element analysis. Two of the leading practitioners of their application to microelectronic packaging are Suhir [42,43] and Lau [9]; their publications are highly recommended.

8.5.1 Introduction

The source of many packaging processing defects and reliability problems is thermal stress. In our first encounter with internal stress we saw (Sect. 3.3.2.2) how thermal stress could develop in a single material when constrained. Thermal stresses can also arise in so-called thermostat or bimetallic strip structures, consisting of two different materials in intimate contact. Normally it is assumed that the thermostat is unstressed at some reference temperature. Stress then develops in the thermostat as it is either cooled or heated to the use temperature because the thermal expansion coefficients of the two materials differ. A film of SiO2 on silicon is such a thermostat structure that was discussed in connection with oxidation (Sect. 3.3.2.4). As noted on earlier occasions, Eq. 8-1 (or 3–8) yields the stress magnitude.

Stress can also develop in a bilayer structure by other than thermal means. Epitaxial mismatch and film-growth processes are examples of intrinsic sources of internal stress in film/substrate bilayers. The Stoney formula (Eq. 3-10) describes the bowing of the bilayer in terms of the stress. Thermal stresses will also cause bilayers to bow. Thus by combining Eqs. 8-1 and 3-10, the predicted radius of curvature, R, of the combination is given by

(8-6)R =(1-νf)Esds26( 1-νs)dfEf[αs-αf ](ΔT),

where f and s refer to film and substrate, respectively, and ΔT is the temperature difference.

The packaging structures we are about to consider differ from thermostats in that they contain three, not two, contiguous layers. Even though packaging layers are thick compared to thin films, the same principles of mechanics apply when considering response to loading. Thermal stress problems are generally complex, requiring knowledge of elasticity theory and finite element analysis. Two of the leading practitioners of their application to microelectronic packaging are E. Suhir (39,40) and J. H. Lau (9); their publications are highly recommended.

Abstract

The preceding chapters have introduced the devices, processing defects, and yields of electronic products that will now see service. Chapter 4 prepared us to expect product failures and provided mathematical tools that enable future performance to be predicted. From now until the end of Chapter 10, we shall be primarily concerned with the detailed microscopic mechanisms that cause these products to degrade in use. We have already noted (Section 1.3.1) that virtually all failures in electronic materials and devices are the result of the physical movement of atoms or charge carriers from benign locations associated with normal behavior to other sites where they contribute to creating or enlarging defects that lead to component malfunction. Because solids are often not in thermodynamic equilibrium, atoms feel compelled to move or react. Thus, silicon and aluminum should theoretically revert to SiO2 and Al2O3 in air at room temperature, while dopants at junctions should intermix in response to thermodynamic imperatives. But fortunately, for the most part, these and other scenarios for change and reaction in chemically unstable materials, interfaces, and structures do not occur. The low operating temperatures involved essentially reduce reaction rates to negligible levels. Nevertheless, there are other material combinations and forces present that do pose threats to reliability because the chemical and physical changes they induce are on a scale comparable to device or component feature dimensions.

5.1 INTRODUCTION

The preceding chapters have introduced the devices, processing defects, and yields of electronic products that will now see service. Chapter 4 prepared us to expect product failures and provided mathematical tools that enable future performance to be predicted. From now until the end of Chapter 10 we shall be primarily concerned with the detailed microscopic mechanisms that cause these products to degrade in use. We have already noted (Sect. 1.3.1) that virtually all failures in electronic materials and devices are the result of the physical movement of atoms or charge carriers from benign locations associated with normal behavior to other sites where they contribute to creating or enlarging defects that lead to component malfunction. Because solids are often not in thermodynamic equilibrium, atoms feel compelled to move or react. Thus, silicon and aluminum should theoretically revert to SiO2 and Al2O3 in air at room temperature, while dopants at junctions should intermix in response to thermodynamic imperatives. But fortunately, for the most part these and other scenarios for change and reaction in chemically unstable materials, interfaces, and structures do not occur. The low operating temperatures involved essentially reduce reaction rates to negligible levels. Nevertheless, there are other material combinations and forces present that do pose threats to reliability because the chemical and physical changes they induce are on a scale comparable to device or component feature dimensions.

In this chapter we primarily deal with phenomena attributable to atomic diffusional motion on the chip level. This should be distinguished from other transport effects treated elsewhere, i.e., electron (Chap. 6), ionic (Chap. 7), and stress-induced flow of solder (Chap. 9). Effects of atomic diffusion include compound formation, precipitation reactions, void formation, alloying, contact and interconnect reactions, and general degradation of the metallization. Related examples involve environmentally induced ion migration during corrosion and the permeation of water through plastic packages.

It is a primary objective of this chapter to predict the time dependence of the visible manifestations of failure based on the mass transport models that describe them. Metals are the major culprit associated with mass transport–induced reliability problems at both chip and packaging levels. Degradation and failure phenomena due to interdiffusion, compound formation, electromigration, and contact reactions are some of the effects modeled in this chapter.

10.1.2.2 Manufacturing processes and mechanical damage

Defects originating in manufacturing (processing, installation, assembly, etc.) and developing into mechanical damage are often hard to detect because of the location and placement involved.

These kinds of defect are also often regional, i.e. affecting a considerable area (many load paths), and therefore constitute a serious threat to fail-safe integrity. If the result also includes reduced structural properties such as strength, stiffness, damage resistance, damage growth rates and ‘residual strength’, the situation is unsafe and described by the equation given below (Equation (10.4)). The combined event describes a situation where a serious process failure renders the structural strength and damage tolerance properties below requirements, is not detected in process control or in quality control and produces mechanical damage and loss of limit integrity and failure. This combined event is described in Equation (10.4), and Example 10.5 contains an analysis that illustrates the consequences of using realistic values supporting the safety objective.

(10.4)P(A¯MD)=P(X¯MTiVi3P¯C Q¯CU¯LtX¯tD¯ UA¯T)=P(A¯T|U¯LtX¯tD¯UP¯CQ¯CX¯MTiVi3)·P(Q¯C|P¯CX¯MTiVi3)··P(P¯C|X¯MTiVi3)·P(Vi3|T iX¯M)·P(Ti|X¯M )·P(X¯M)·P(U¯ Lt|X¯tD¯UX¯MT iVi3)·P(D¯U|X¯tX¯MTiVi3)·P(X¯t|X¯MTiVi3)

The following events participate:

X¯M: processing defect in manufacturing

Ti: type of defect reduced strength and damage tolerance

Vi3: extent of damage

P¯C: failed process control

Q¯C: failure of quality control

U¯Lt: loss of limit integrity at time t

X¯t : mechanical damage present

D¯U: damage size larger than ultimate requirement

A¯T: failure at time T

A¯MD: failure due to manufacturing defect.

7.2.4 Processing effects

The behavior of GFRP composites depends strongly on the manufacturing process and processing defects. The most commonly used manufacturing techniques for FRP structural components used in civil engineering are pultrusion, vacuum-assisted resin transfer molding (VARTM), and filament winding. Through comparing the flexural fatigue behavior of unidirectional GFRP composites, Salvia et al. (1997) showed that filament winding is slightly better than molding, and much better than pultrusion. However, pultrusion is the most economically efficient technology for making GFRP structural members for civil engineering applications.

Fiber undulation is a key parameter characterizing the fatigue of FRP composites when different manufacturing techniques are used. Factors contributing to fiber undulation during the manufacturing process include laminate thickness, fiber waviness, cavities between fiber bundles, stitch stress risers, and flaws (such as microcracking and slight delamination) in the as-processed state. As shown in Fig. 7.1, pultruded E-glass/epoxy laminates with fiber undulation were shown to have lower S–N curves than those of unidirectional and cross-ply laminates manufactured from pre-impregnated E-glass/epoxy tape which has very little fiber undulation (Phifer 1998).

The degree of cure of polymer resin is another key processing factor that influences the fatigue and durability of FRP composites. The composite's glass transition temperature (Tg) and microstructure have been shown to correlate with the degree of cure of its polymer resin. For pultruded composites, the cure of polymer resins is usually high due to the heating of pultrusion die during the manufacturing process; thus less post-curing effects can be observed for pultruded composites. For composites made through the VARTM process at room temperature, the post-curing can have significant effects on the mechanical and fatigue properties. Examination of ambient cured VARTM E-glass/vinyl-ester resin composites by Cain et al. (2006) showed that their mechanical properties are significantly affected by the degree of cure. Their studies suggest that, in practice, the need for VARTMed structural composites to have stable and predictable mechanical properties necessitates the use of a post-cure regime.

1 INTRODUCTION

Axis-symmetric composite structures are widely used in aerospace applications. Among the common processing defects, delaminations and voids happen to be most predominant.

It is well known that an ideal two dimensional laminar defect like a delamination can not be detected by x-ray radiography. However, real delaminations often have finite but small thicknesses In such cases, tangential x-ray radiography is widely used for generating permanent record of defects present in the component, particularly in situations where ultrasonic C-scan facility is not available.

However, even detectability and relative comparison of defects by application of this technique need to be accepted with some amount of caution. The crux of the problem here lies in the fact that every single x-ray beam propogating through the component happens to have a different path length, depending on the component geomentry and also on the source-component-film configuration.

An attempt has been made in this paper (a) to clearly understand the scope and limitation of this technique in terms of detectability of defects with variable size and location (b) to develop a methodology for selecting optimum radiographic parameters.

The work presented here deals with an axis-symmetric cfrp shell of specific dimensions. However, the methodology adopted here is quite general in its scope and can be used as well for any other component.

3.6.4 Intelligent Tour Inspection System Functions of Transmission Lines

System functions consist mainly of dynamic information, archive management, defect management, operation management, interactive platform, basic data, background management, and system maintenance.

3.6.4.3 Defect management

A processing flow chart for line defects is shown in Fig. 3.49.

Figure 3.49. Treatment flow of line defect. (A) Routine treatment flow of defect, (B) treatment flow of defect after the event.

In analyzing a treatment flow chart for a defect, the functions of defect management modules are split. The internal function module diagram for defect management is shown in Fig. 3.50.

Figure 3.50. Internal function modules of defect management.

3.6.4.4 Operation management

The flow module of operation management is as shown in Fig. 3.51. Standardized operation instructions are issued for each model. Users that have the system administrator right can increase, delete, modify, and edit models in the server; all the users who use the system can obtain the models that they want from the server, and edit field operation instructions; the edited field operation instructions need to be examined and approved by the competent department. After the field operation instructions are examined, approved, and passed, they can be downloaded to the PDA, or directly printed and captured as paper instructions. Modular construction is used to prepare for operation instruction in the system. When the operation instructions are prepared, submodules or submodule data can be called from the different models, which reduces repeated inputting work for data, and decreases the workload of frontline staff.

Figure 3.51. Flow modules of operation management.