Diagnosis and Solution of Pneumatic Conveying Bend Problems: Application of TRIZ-DEMATEL Coupling Technology

Abstract

Mining, mineral processing, and power generation are just a few of the industries that have made extensive use of pneumatic conveying systems in recent years. The market for pneumatic conveying is anticipated to grow to a value of $30 billion by 2025. However, problems with the pneumatic conveying process are common and include coal particle damage, pipe wall wear, and excessive system energy consumption. A new systematic framework for decision-making is created by combining the Theory of Inventive Problem Solving (TRIZ) with the Decision-Making Trial and Evaluation Laboratory (DEMATEL). This methodology employs TRIZ-Ishikawa to determine the underlying causes of issues from six different perspectives. It then suggests remedies based on TRIZ technical contradictions and uses DEMATEL to examine how the solutions interact to determine the best course of action. This study confirms the viability of this approach in recognizing fundamental contradictions, producing workable solutions, and reaching scientific conclusions in challenging issues by using instances such as wear and tear, obstructions, and low conveying efficiency in pneumatic conveying system elbows. It offers particular references for real engineering projects and suggests practical solutions like employing quick-release flanges and installing multiple sets of airflow regulators.

1. Introduction

The coal, chemical, and energy sectors all make extensive use of pneumatic conveying [1,2,3,4,5]. Low conveying efficiency and excessive energy consumption are problems with conventional pneumatic conveying systems [6,7]. Among these, elbows—which are crucial parts—experience an unequal distribution of velocity in the gas–solid two-phase flow, which increases the material’s local erosion of the pipe walls. This drastically shortens the pipeline’s service life by causing wear rates that are three to five times higher than those of straight pipe sections. Pneumatic conveying bends have been optimized in numerous studies [8,9,10,11], but no study has used creative thinking to analyze the problems with these bends.

As a highly influential innovation technique, the Theory of Inventive Problem Solving (TRIZ) has proven its potent potential in invention [12,13,14]. TRIZ is more successful in recognizing issues and offering researchers workable answers than other approaches to problem-solving like mind mapping and brainstorming [15]. TRIZ was used by Vicente-Gomila et al. [16] to investigate solar cell technology. Chou [17] gave an example of how TRIZ may support researchers in solving problems and designers in creating novel products. The TRIZ theory’s idea of technical contradictions was used by Anahita et al. [18] to address issues that faced architects. Shao et al. [19] creatively designed a bag filter by leveraging the technological inconsistencies in TRIZ. Wu et al. [20] also used the technical contradictions in TRIZ to analyze the problems in the green industry. TRIZ-Ishikawa was used by Karim et al. [21] to pinpoint six major causes of road accidents, allowing researchers to examine the issue from several angles. As a result, TRIZ’s debut has changed how people approach problem-solving [22,23,24].

By determining the degree of interaction between different components, the Decision-Making Trial and Evaluation Laboratory (DEMATEL) simplifies the structure of a system and highlights important factors [25]. The DEMATEL method was employed by Johan et al. [26] to determine the optimal approach for resolving issues related to the green supply chain. Guo et al. [27] established an evaluation system and chose the best course of action for preventing collision incidents using the DEMATEL approach. Zheng et al. [28] evaluated the prevalence of flood issues using DEMATEL. In order to improve rehabilitation levels and service quality, Yuan et al. [29] evaluated issue models using DEMATEL. DEMATEL was utilized by Zhao et al. [30] to evaluate the connections between different elements in order to give each client better services. As demonstrated, DEMATEL is capable of efficiently ranking several strategies [31] in order to identify the best way to solve an issue.

The curved pipes of pneumatic conveying systems have not yet been analyzed using TRIZ and DEMATEL, despite the fact that they have been successfully used in numerous instances. Although TRIZ can assist researchers in finding solutions [32], it is unable to analyze complex difficulties because of its limited capacity to address complex problems [33]. In contrast, DEMATEL can effectively rank several tactics [34], something that TRIZ cannot do. Our team used TRIZ and DEMATEL in tandem to solve the pneumatic conveying bent pipes problem based on the aforementioned concerns. In order to address the drawback of TRIZ, which is that it can be challenging to optimize solutions once they are generated, TRIZ-Ishikawa was used to thoroughly analyze the issue in the pneumatic conveying system. TRIZ analysis determined the underlying causes and suggested solutions, and DEMATEL measured the interactions between the solutions. A methodological reference for the optimization of comparable engineering systems was also provided by this work, which confirmed the efficacy of the combined use of TRIZ and DEMATEL in complicated engineering issues.

The research techniques used are described in Section 2 of this work. In order to determine the underlying causes of the elbow pipe problems in the pneumatic conveying system, Section 3 first examines the six pillars of the system: material, time, function, information, field (the means of material interaction [35]), and space. This analysis is performed using the TRIZ-Ishikawa framework. The TRIZ approach is then used to provide 19 solution strategies that address five contradictions. Section 4 examines the relationships between the 19 TRIZ-proposed solution strategies, assesses them, and chooses the best one using the DEMATEL approach.

2. Research Methodology

2.1. Flowchart

The study consisted of three phases, structured as shown in Figure 1.

2.2. The TRIZ Technology Paradox

As indicated in

Table 1. TRIZ Engineering Parameters List for Resolving Contradictions.

Engineering Parameters
1. Weight of moving objects	14. Strength	27. Reliability
2. Weight of a stationary object	15. Persistence of moving objects	28. Accuracy of measurements
3. Length of moving object	16. Persistence of stationary objects	29. Manufacturing accuracy
4. Length of stationary object	17. Temperature	30. Harmful factors acting on objects
5. Area of the moving object	18. Luminance	31. Harmful side effects
6. Area of a stationary object	19. Energy for moving objects	32. Manufacturable
7. Volume of moving objects	20. Energy for non-mobile objects	33. Ease of use
8. Volume of a stationary object	21. Power (output)	34. Restorative
9. Speed	22. Waste of energy	35. Adaptation
10. Force	23. Material waste	36. Complexity of equipment
11. Tension/Pressure	24. Loss of information	37. Complexity of control
12. Geometry	25. Waste of time	38. Degree of automation
13. Stability of the objects	26. Total amount of substance	39. Capacity/productivity

, TRIZ technical contradictions establish a database of known remedies [36] for this issue. Improvement of one parameter frequently leads to the degradation of another [37]. The creative concepts indicated in

Table 2. List of TRIZ inventive principles for deriving solutions.

Principles of Invention
1. Splitting	15. Dynamic	29. Pneumatic or hydraulic
2. Extraction	16. Partial or excessive movement	30. Elastic membrane or film
3. Principle of Localized Mass	17. Change to a new dimension	31. Porous materials
4. Asymmetry	18. Mechanical vibration	32. Color
5. Merger/combination	19. Periodic movements	33. Homogeneity/conformity
6. Versatility/multifunctionality	20. Continuity of effective movement	34. Discarded and recycled parts
7. Interleave	21. Rapid movements	35. Performance Transformation
8. Principle of weight compensation	22. Turning harm into good	36. Phase Change
9. Pre-emptive counteraction	23. Giving back	37. Thermal expansion
10. Pre-action	24. Mediation	38. Strong oxidation
11. Precautionary	25. Self-help	39. Principle of Inert Environment
12. Isotropy	26. Reproduction	40. Composites
13. Reverse Action	27. Replacement by cheaper and shorter life
14. Curve Surfacing	28. Principle of mechanical system substitution

must be used to resolve each conflict in Table 1.

2.3. DEMATEL

A decision-making aim has n factors, which are represented in

Table 3. Influence Relationship Assessment Scale for Factors within the System.

Relationships of Influence	Not Have	Slightly Less Than	Center	Unyielding	Extremely Strong
Scale	0	1	2	3	4

as F₁, F₂,…, F_n. The degree of mutual influence between elements is assessed in this research using a 0~4 scoring method, which necessitates expert opinion as data input [38]. Effective decisions can only be reached by consensus among specialists [39]. Formulas (1) and (2) are used to calculate the direct influence matrix A. a_ij = 0 if factors F_i and F_j have no effect on one another.

$$A={[a_{ij}]}_{n\times n}$$

(1)

$$A=\left(\begin{array}{cccc}0& a_{12}& \cdots & a_{1n}\\ a_{21}& 0& \cdots & a_{2n}\\ ⋮& ⋮& \ddots & ⋮\\ a_{n1}& a_{n2}& \cdots & 0\end{array}\right)$$

(2)

The direct influence matrix B is derived from the direct influence matrix A using Formulas (3)–(5):

$$B={[b_{ij}]}_{n\times n}$$

(3)

$$B={\displaystyle \frac{A}{\underset{1\le i\le n}{\max }{\displaystyle \sum _{j=1}^n{a}_{ij}}}}$$

(4)

$$\underset{1\le i\le n}{\max }{\displaystyle \sum _{j=1}^n{a}_{ij}}=1$$

(5)

Based on the direct influence matrix B, the comprehensive influence matrix C can be calculated using Formulas (6) and (7).

$$C={[c_{ij}]}_{n\times n}$$

(6)

$$C=B\times {(I-B)}^{-1}$$

(7)

Based on the comprehensive influence matrix C, the influence degree D_i and the affected degree R_i of each system factor are calculated using Formulas (8) and (9), respectively, to determine the direct and indirect influences between factors [40].

$$D_i={\displaystyle \sum _{j=1}^n{c}_{ij}\left(i=1,2,\cdots n\right)}$$

(8)

$$R_i={\displaystyle \sum _{i=1}^n{c}_{ij}\left(j=1,2,\cdots n\right)}$$

(9)

The centrality and causality are calculated based on the influence degree and affected degree corresponding to each factor in the system, as well as Formulas (10) and (11).

$$P_i=D_i+R_i$$

(10)

$$Q_i=D_i-R_i$$

(11)

Among these, Q_i stands for causality; a positive Q_i value means that the factor influences other factors in the system, and a negative Q_i value means that the factor is influenced by other factors in the system. P_i, on the other hand, represents centrality, reflecting the overall scenario where a factor acts as both an “influence source” and an “affected object”. A thorough examination of each factor’s centrality P_i and causation Q_i is carried out, with the centrality P_i serving as the x-axis and the causality Q_i as the y-axis. The main components of the system are determined by plotting a causal link diagram [41].

3. Heuristic Reasoning for the Pneumatic Conveying Bend Challenge

3.1. Determination of Root Cause Using TRIZ-Ishikawa

Interviews with 15 university experts—9 from Northeast Electric Power University, which covers the fields of thermal engineering, new energy science and engineering, and TRIZ theory application, which is primarily responsible for evaluating the scientific validity of conflict identification and solutions from a theoretical perspective—and six from industrial companies, who were engineers specializing in the design and maintenance of pneumatic conveying systems, were conducted in order to align with industrial practical needs. This analysis focused on the underlying causes of the aforementioned pneumatic conveying issues. We have determined the underlying causes of the six types of problems that arise in pneumatic conveying systems, as shown in Figure 2.

3.2. Contradictions in Pneumatic Conveying Bends

By evaluating the fundamental causes of the above pneumatic conveying problems and interviewing 15 university experts, we discovered five standard contradictions, and the outcomes of determining engineering parameters for each contradiction are displayed in

Table 4. Standard Contradictions and Engineering Parameters of Pneumatic Conveying Elbow Systems.

Standard Contradiction	Gestion	Improvement (I) and Worsening (W)	Engineering Parameters
Standard contradiction 1	Improvement of conveying efficiency of pneumatic conveying	I: Increased conveying efficiency W: Increased wear and tear	9. Speed 14. Strength
Standard contradiction 2	Strengthening of curves	I: Increased strength of the bend W: Increase in local resistance at the bend	14. Strength 10. Force
Standard contradiction 3	Adjustment to the properties of the material to prevent elbow blockage	I: Adaptation to material properties reduces clogging W: Increased costs	35. Adaptation 26. Total amount of substance
Standard contradiction 4	Optimizes bend radius while meeting installation space requirements	I: Reduced installation space after optimizing bend radius W: Impact on conveying performance	5. Area of moving objects 13. Stability of the objects
Standard contradiction 5	Improving the simplicity of bend maintenance	I: Increased ease of maintenance W: Poor sealing leads to loss of pneumatic conveying particles	33. Ease of use 23. Material waste

.

• Standard contradiction 1: Conveying efficiency and wear
• Standard contradiction 2: Bend strength and resistance
• Standard contradiction 3: Elbow obstruction and material qualities
• Standard contradiction 4: Bend radius and installation space
• Standard contradiction 5: Ease of maintenance and sealing

The incongruity between wear and conveying efficiency is standard contradiction 1 in Table 4. An increase in air velocity is necessary to improve conveying efficiency, but doing so will accelerate elbow wear by aggravating the scouring of the material on the elbow’s inner wall. When the improvement (I) and Worsening (W) parameters are determined, the improvement (I) parameter (improved conveying efficiency) falls under the “speed” category, while the Worsening (W) parameter (increased wear) falls under the “strength” category. This also applies to other factors.

3.3. Innovative Approaches to Addressing the Difficulties of Pneumatic Conveying Bends

As seen in

Table 5. Engineering Parameters and Inventive Principles of Pneumatic Conveying Elbow Systems.

Standard Contradiction	Engineering Parameters	Principles of Invention
Standard contradiction 1	Improvement (I): 9. Speed Worsening (W): 14. Strength	8. Principle of weight compensation 3. Principle of localized quality 26. Principle of Reproduction 14. Curve Surfacing Principle
Standard contradiction 2	Improvement (I):14. Strength Worsening (W): 10. Force	18. Principle of mechanical vibration 10. Pre-action principle 3. Principle of Localized Mass 14. Curve Surfacing Principle
Standard contradiction 3	Improvement (I): 35. Adaptation Worsening (W): 26. Total amount of substance	3. Principle of localized quality 35. Performance Transformation Principle 15. Dynamic principle
Standard contradiction 4	Improvement (I): 5. Area of moving objects Worsening (W): 13. Stability of the object	11. Precautionary principle 2. Extraction Principle 13. Reverse Action Principle 39. Principle of Inert Environment
Standard contradiction 5	Improvement (I): 33. Ease of use Worsening (W): 23. Material waste	28. Principle of mechanical system substitution 32. Color principle 2. Extraction Principle 24. Mediation Principle

, the TRIZ matrix is used to produce principles of invention that match the engineering parameters once they have been established [42,43].

The relationship between engineering parameters, standard conflicts, and the corresponding inventive principles is displayed in Table 5. For instance, the four invention concepts of “8. Weight Compensation Principle”, “3. Local Mass Principle”, “26. Duplication Principle”, and “14. Curve Surface Principle” are correlated with the improvement (I) and degradation (W) parameters of standard contradiction 1.

Standard contradiction 1 can be resolved utilizing the four innovation principles derived from TRIZ, which take into account both the improvement (I) parameters and the deterioration (W) parameters. Four innovation principles are represented by standard contradictions 2, 4, and 5, while three invention principles are represented by standard contradiction 3, as indicated in Table 5.

Table 6. Innovative principles to cope with the contradictions of pneumatic conveying.

Contradictions Faced	Principles of Invention	Principles of Innovation Derived from Pneumatic Conveying Heuristic Reasoning
High-speed conveying improves conveying efficiency, but it also increases friction between the material and the pipe’s inner wall.	8. Principle of weight compensation 3. Principle of localized quality 26. Principle of Reproduction 14. Curve Surfacing Principle	A1. Installing many airflow regulators that are identical at different pipeline sites. A2. Putting an appropriate amount of lubricant on the area that is causing the most friction. A3. Use localized cooling techniques in specific pipe sections that are subject to high levels of wear and tear in order to lessen the worsening of material characteristics and increased wear caused by high temperatures. A4. Reproduction of the wear-resistant material coating: covering the entire pipe’s inner wall with several layers of the same material coating. A5. Use of flexible, curving tubing, which allow for some deformation as a cushioning effect.
Boost the bend’s strength, but do so at the expense of increased localized resistance.	18. Principle of mechanical vibration 10. Pre-action principle 3. Principle of Localized Mass 14. Curve Surfacing Principle	B1. At the bends, vibrators are positioned to produce resistance in the pipe, which increases amplitude. B2. By enabling materials to enter the bent pipe smoothly, pre-buffer silo placement reduces the impact’s local resistance. B3. Localized use of high-efficiency bent pipe designs with high-efficiency infusion reduces the advantages of resistance.
Specialized designs and expensive materials are used to lessen congestion, albeit this may lead to increased costs.	3. Principle of localized quality 35. Performance Transformation Principle 15. Dynamic principle	C1. Turn manual monitoring into intelligent regulation and monitoring by putting in place an intelligent control system. C2. Replace conventional thin-phase pneumatic conveying with dense-phase or pulse pneumatic conveying. C3. Installing sensors allows for dynamic, real-time material property monitoring.
Optimize bend radii to minimize installation space, but conveyance performance may decrease as a result.	11. Precautionary principle 2. Extraction Principle 13. Reverse Action Principle 39. Principle of Inert Environment	D1. At the most abrasive location, an auxiliary air inlet is already constructed, and the airflow provides secondary energy to move the particles forward. D2. Pre-simulate and examine bends of various radii using fluid dynamics simulation software. D3. Finding the causes of pressure loss and improving bend structures to lessen pressure loss from changing the radius D4. Make the switch to a flexible connection from a conventional, hard one. D5. By introducing nitrogen and other inert gases to create an inert atmosphere that prevents raw materials from oxidizing and deteriorating, you can lower transport performance.
To make maintenance easier, the piping system might be simplified; however, this may result in inadequate sealing and particle loss.	28. Principle of mechanical system substitution 32. Color principle 2. Extraction Principle 24. Mediation Principle	E1. Use quick-release flanges and make sure sealing gaskets are optimized to preserve sealing. E2. Apply fluorescent color coating to the sealing area, causing the particles to change color when leaking. E3. Install intermediate barriers with air curtain sealing in regions where pipeline leaks are common.

displays the outcomes of a debate about these inventive principles in respect to the real challenge.

4. Analysis and Discussion of Results

As shown in

Table 7. The system’s comprehensive impact matrix C.

	A1	A2	A3	A4	A5	B1	B2	B3	C1
A1	0	0.091	0.099	0.108	0.118	0.091	0.008	0.009	0.101
A2	0	0	0.091	0.099	0.108	0	0	0	0
A3	0	0	0	0.091	0.099	0	0	0	0
A4	0	0	0	0	0.091	0	0	0	0
A5	0	0	0	0	0	0	0	0	0
B1	0	0	0	0	0	0	0.091	0.099	0.108
B2	0	0	0	0	0	0	0	0.091	0.099
B3	0	0	0	0	0	0	0	0	0.091
C1	0	0	0	0	0	0	0	0	0
C2	0	0	0	0	0	0	0	0	0
C3	0	0	0	0	0	0	0	0	0
D1	0	0	0	0	0	0	0	0	0
D2	0	0	0	0	0	0	0	0	0
D3	0	0	0	0	0	0	0	0	0
D4	0	0	0	0	0	0	0	0	0
D5	0	0	0	0	0	0	0	0	0
E1	0	0	0	0	0	0	0	0	0
E2	0	0	0	0	0	0	0	0	0
E3	0	0	0	0	0	0	0	0	0
	C2	C3	D1	D2	D3	E1	E2	E3	E4	E5
A1	0.009	0.01	0.231	0.042	0.05	0.059	0.069	0.372	0.088	0.05
A2	0	0	0.118	0.021	0.025	0.03	0.035	0.042	0.018	0.007
A3	0	0	0.108	0.02	0.023	0.027	0.032	0.038	0.016	0.006
A4	0	0	0.099	0.018	0.021	0.025	0.03	0.035	0.015	0.006
A5	0	0	0.091	0.017	0.02	0.023	0.027	0.032	0.014	0.005
B1	0.01	0.011	0.012	0.002	0.003	0.003	0.004	0.105	0.02	0.013
B2	0.009	0.01	0.011	0.002	0.002	0.003	0.003	0.013	0.003	0.002
B3	0.008	0.009	0.01	0.002	0.002	0.002	0.003	0.012	0.003	0.002
C1	0.091	0.099	0.108	0.02	0.023	0.027	0.032	0.129	0.033	0.018
C2	0	0.091	0.099	0.018	0.021	0.025	0.03	0.035	0.015	0.006
C3	0	0	0.091	0.017	0.02	0.023	0.027	0.032	0.014	0.005
D1	0	0	0	0.182	0.215	0.254	0.3	0.355	0.151	0.06
D2	0	0	0	0	0.182	0.215	0.254	0.3	0.205	0.064
D3	0	0	0	0	0	0.182	0.215	0.254	0.173	0.055
D4	0	0	0	0	0	0	0.182	0.215	0.147	0.046
D5	0	0	0	0	0	0	0	0.182	0.124	0.039
E1	0	0	0	0	0	0	0	0	0.182	0.124
E2	0	0	0	0	0	0	0	0	0	0.182
E3	0	0	0	0	0	0	0	0	0	0

, non-zero values in the composite impact matrix C affect the other strategies directly or indirectly.

Centrality P_i and weight were used as indicators to judge the importance of the factors, and the most influential key enablers were identified [44]. As demonstrated in

Table 8. Results of DEMATEL calculations.

	Degree of Influence Di	Influenced Degree Ri	Centrality Pi	Reason Degree Qi	Wights	Order of Centrality	Factor Attributes
A1	1.48	0	1.48	1.48	0.083	3	Contributory factor
A2	0.574	0.057	0.631	0.517	0.035	11	Contributory factor
A3	0.45	0.122	0.572	0.329	0.032	12	Contributory factor
A4	0.344	0.196	0.54	0.148	0.03	13	Contributory factor
A5	0.252	0.282	0.533	−0.03	0.03	14	Outcome factor
B1	0.389	0.057	0.445	0.332	0.025	15	Contributory factor
B2	0.213	0.065	0.278	0.148	0.016	18	Contributory factor
B3	0.136	0.131	0.268	0.005	0.015	19	Contributory factor
C1	0.538	0.264	0.802	0.274	0.045	10	Contributory factor
C2	0.344	0.095	0.44	0.249	0.025	16	Contributory factor
C3	0.252	0.167	0.418	0.085	0.023	17	Contributory factor
D1	1.318	0.685	2.002	0.633	0.112	2	Contributory factor
D2	0.986	0.316	1.303	0.67	0.073	6	Contributory factor
D3	0.674	0.522	1.196	0.152	0.067	8	Contributory factor
D4	0.433	0.788	1.222	−0.355	0.068	7	Outcome factor
D5	0.247	1.134	1.381	−0.887	0.077	4	Outcome factor
E1	0.204	1.914	2.117	−1.71	0.118	1	Outcome factor
E2	0.113	1.314	1.427	−1.2	0.08	5	Outcome factor
E3	0	0.84	0.84	−0.84	0.047	9	Outcome factor

, Strategy E1- “Use quick release flanges and make sure sealing gaskets are optimized to preserve sealing” has the highest centrality P_i of 2.117 and weight of 0.118 among the 19 strategies, indicating that there are the most direct and indirect links between factor E1 and other factors. There are more direct and indirect links between factor D1 and other factors, according to the second most influential strategy D1- “At the most abrasive location, an auxiliary air inlet is already constructed, and the airflow provides secondary energy to move the particles forward” with a centrality P_i of 2.002 and a weight of 0.112. The third most influential strategy, A1- “installing many airflow regulators that are identical at different pipeline sites”, has a centrality P_i of 1.48 and a weight of 0.083, suggesting that adding a spoiler fan through weight compensation can be a viable solution. Furthermore, the following strategies have a higher centrality P_i and weight: D5- “By introducing nitrogen and other inert gases to create an inert atmosphere that prevents raw materials from oxidizing and deteriorating, you can lower transport performance”; E2:- “Apply fluorescent color coating to the sealing area, so that the particles will change color when leaking, Apply fluorescent color coating to the sealing area, causing the particles to change color when leaking” and D2- “Pre-simulate and examine bends of various radii using fluid dynamics simulation software”. The aforementioned indicates that the primary approaches for resolving the pneumatic conveying bends issue are E1, D1, A1, D5, E2, and D2. Figure 3 and Figure 4 display the weights assigned to each component of the evaluation system [45]. Figure 4A to E respectively represent Standard Contradiction 1 to 5 from Table 5.

As seen in Figure 5, a thorough influence relationship diagram of the system’s components is created using DEMATEL. This gives the intricate problems of interconnected elements a distinct framework [46]. There are interacting relationships between the factors, as shown by the lines connecting them. A1 functions as a causal factor in this system, exerting influence, if there are more arrows pointing from A1 to other factors than from other factors to A1; on the other hand, if there are fewer arrows pointing from E3 to other factors than from other factors to E3, then E3 functions as a resultant factor in this system, being influenced. The influence’s magnitude is indicated by the numbers on the arrows.

There are far more arrows pointing to factor A1 from other factors in the diagram than there are pointing to it from other factors. The DEMATEL computation results in Table 8 support this phenomenon: A1 actively drives several aspects in the system, as seen by its positive causality index Q_i = 1.48, influence degree D_i = 1.48, and affected degree R_i = 0. For instance, it has a 0.372 effect on E3 and a 0.231 effect on D1. By stabilizing pipeline gas flow, this can indirectly maximize sealing performance and particle transport power, underscoring its function as a primary causative factor. The result factor E3’s properties are completely the reverse. The majority of the arrows in the picture come from basic elements like A1 and D1, with very few pointing to other aspects. E3 has negative values D_i = 0, R_i = 0.84, and Q_i = −0.84 when combined with the information in Table 8. Other factors mostly control the status of E3, such as A1 minimizing maintenance requirements for E3 by stabilizing airflow and reducing leakage hazards. By accurately quantifying the intensity of this influence, the arrows’ particular numerical values (e.g., 0.372 for A1→E3) allow readers to intuitively evaluate the relevance of factor interactions and provide visual evidence for selecting key solutions in following investigations.

The strategy causality diagram that corresponds to the five conventional inconsistencies is shown in Figure 6a shows that, for strategy A, the centrality P_i of factor A1 is greater than that of factors A2, A3, A4, and A5. This means that, in criterion contradiction 1, the degree of influence of factor A1 on the other factors in the system and the degree of influence of the other factors on factor A1 are both greater than the degree of influence of the other factors on the other factors and the degree of influence of the other factors on them. In conventional contradiction 1, the arrow from factor A1 to factor A2 indicates that factor A1 influences factor A2. The arrows pointing to other factors and the fact that factor A1 is linked to other factors show that factor A1 affects factors A2, A3, A4, and A5. A5 has a negative cause degree Q_i, which is the result factor in the pneumatic conveying system and is influenced by the other factors in the system. A1, A2, A3, and A4 have positive cause degree Q_i values, which are the cause factors in the system and influence the other factors, impacted by additional systemic variables.

The centrality degree Q_i of factor B1 is greater than that of factors B2 and B3 for the B strategy, as shown in Figure 6b. This suggests that B1 is the most influential factor in the standard contradiction 2 because the degree of influence of B1 on the other factors in the system and the degree of influence of the other factors on factor B1 are greater than the degrees of influence of B2 and B3 on the other factors and the other factors on them. The pneumatic conveying system’s cause factors, B1, B2, and B3, all have positive cause degree Q_i and have an impact on other system components.

The centrality P_i of factor C1 is greater than that of factors C2 and C3 for the C strategy, as shown in Figure 6c. This suggests that C1 is the most influential factor in criterion contradiction 3, as the degree of influence of C1 on the other factors in the system and the degree of influence of the other factors on factor C1 are greater than the degrees of influence of C2 and C3 on the other factors and the other factors on them. The pneumatic conveying system’s cause factors, C1, C2, and C3, all have positive cause degrees (Q_i) and have an impact on other system components.

The centrality degree P_i of factor D1 is greater than that of factors D2 and D3 for the D strategy, as shown in Figure 6d. This means that the degree of influence of D1 on the other factors in the system and the other factors’ influence on D1 are greater than the degree of influence of D2 and D3 on the other factors and the other factors’ influence on them. This means that in the standard contradiction 4, D1 is the most influential factor. In the pneumatic conveying system, elements D1, D2, and D3 all have positive degrees of cause Q_i and serve as cause factors that affect other system components. In the pneumatic conveying system, factors D4 and D5, which have all negative cause degrees Q_i, are result factors that have an impact on the system.

Figure 6e shows that for class E strategies, factor E1’s centrality degree P_i is greater than that of factors E2 and E3. This means that the degree of influence of E1 on the other factors in the system, as well as the degree of influence of the other factors on E1, are greater than the degrees of influence of E2 and E3 on the other factors and the other factors on them. This suggests that E1 is the most influential factor in the criterion contradiction 5. In the pneumatic conveying system, variables E1, E2, and E3—all of which have negative cause degree Q_i—are consequent factors that have an impact on the system.

The 19 strategies were ranked, and

Table 9. The final strategic decision regarding this conflict.

Rankings	Strategy	Conflicting Views	Response
1	E1	Ease of maintenance and sealing	Use quick release flanges and make sure sealing gaskets are optimized to preserve sealing.
2	D1	Installation space and bend radius	At the most abrasive location, an auxiliary air inlet is already constructed, and the airflow provides secondary energy to move the particles forward.
3	A1	Conveying efficiency and wear	Installing many airflow regulators that are identical at different pipeline sites.
4	D5	Installation space and bend radius	By introducing nitrogen and other inert gases to create an inert atmosphere that prevents raw materials from oxidizing and deteriorating, you can lower transport performance.
5	E2	Ease of maintenance and sealing	Apply fluorescent color coating to the sealing area, causing the particles to change color when leaking.
6	D2	Installation space and bend radius	Pre-simulate and examine bends of various radii using fluid dynamics simulation software.

summarizes the top strategies for handling the bending issue in pneumatic conveying systems.

This study set up a matching experimental platform to confirm the accuracy of the auxiliary inlet addition position. Polyvinyl chloride (PVC) was used as the pipe material. The tiny size of the coal powder particles made it difficult to see their movement paths. Blue foam balls around 2.5 cm in diameter were used to trace solid particles. In order to determine the maximum wear position on the bent pipe, simulation and experimental results were compared. About 35.6° was the largest central wear angle. This validates the correctness of the highest wear location by showing that the numerical simulation results match experimental conditions, as shown in Figure 7.

As seen in Figure 8 and Figure 9, an extra air inlet was installed where the bent pipe is most worn. The highest wear rate was found to be 37% when the impacts of supplementary air intake were compared at various inclination degrees between 40° and 80°. With a maximum decrease of 9.5%, the average pressure drop at the elbow could be minimized at an inclination angle of 70°. With a maximum increase of 27.3% and an average flow velocity increase of 20.1%, the addition of an auxiliary air intake considerably raises the center axial velocity of particles at the elbow outlet. Through studies on bent pipes, as illustrated in Figure 10 and Figure 11, our team confirmed the efficacy of the pre-added auxiliary air intake by demonstrating that it greatly decreased the collision rate between the particle flow and the pipe wall’s outer side.

5. Conclusions

Based on a combined TRIZ and DEMATEL approach for the study of pneumatic conveying elbows, we draw the following conclusions:

(1)

By integrating the pneumatic conveying system using TRIZ-Ishikawa, we were able to analyze five key contradictions, such as conveying efficiency and wear, elbow strength and resistance, etc., and identify the root causes of problems in the system from six perspectives. For every conflict in the elbows of the pneumatic conveying system, we produced matching engineering characteristics and invention concepts using TRIZ technology, yielding 19 possible solutions. These solutions cover a wide range of topics, such as the use of unique materials, process optimization, and equipment upgrades.

(2)

The 19 solutions suggested by TRIZ were best chosen using the quantitative ranking method known as DEMATEL. The best ways to deal with the problems related to pneumatic conveying elbows were found to be “using quick-release flanges”, “pre-installing auxiliary air inlets at the most severely worn areas”, and “installing multiple identical airflow control devices at different locations along the pipeline.”

(3)

The usefulness of the pre-added auxiliary air intake was confirmed by lowering the collision rate between the particle flow and the outside of the bent pipe wall by placing it where the bent pipe was most worn. The center axial velocity was raised by up to 27.3%, the maximum wear rate was decreased by 37%, and the average pressure drop was decreased by up to 9.5%. This established a methodological foundation for resolving related engineering problems and confirmed the efficacy of integrating TRIZ and DEMATEL in resolving complicated engineering system difficulties.