Demonstration of the Growth in Added Values for Industrial Products Manufacturing

It should be obvious that the classification of organizational processes and sub-processes and extracting their respective Cpmk can help determine the action plans to increase the processes capability eventually leading up to added values in triple organizational processes. Note that the impact of applying the selected QET (in the form of an action plan) can result in added values for industrial products manufacturing. A schematic representation is provided in Figure 4.2. Also, a sample action plan with details is provided in Table 4.3.

Creating added values by applying QET

FIGURE 4.2 Creating added values by applying QET.

Action Plan for Creating Added Values in Some Organizational Processes

TABLE 4.3

Process

^pmk

(before)

Plan details

Cpmk

(after)

Orders

0.32

• Applying related techniques of statistical techniques (ST) at all levels of reception e.g., descriptive statistics

0.52

Planning

0.29

• Applying related techniques of quality engineering techniques including statistical techniques (ST) such as statistical tolerances, simulation, and analysis of time series; and such non-statistical techniques (NT) as QFD, VE, and DFMEA

0.49

Manufacturing

0.20

• Applying related techniques of statistical techniques (ST) at all levels of production e.g., descriptive statistics and PFMEA

0.2S

Quality Control

0.17

  • • Calibrating all tools related to quality control
  • • Applying such related techniques of statistical techniques (ST) as SPC at all levels of control
  • • Applying such related techniques of non- statistical techniques (NT) as COQ at all levels of control
  • • Considering risks and opportunities in control inputs and outputs

0.25

Customer

0.32

  • • Anticipating customer requirements
  • • Applying related techniques of SPC in assessing customer satisfaction
  • • Considering risks and opportunities in customer requirements

0.45

Productivity

Management

0.33

  • • Manufacturing resources management
  • • Planning and manufacturing control
  • • Manufacturing timing management
  • • Quality system management
  • • Projects control management

0.52

Sustainability

Management

0.33

  • • Manufacturing processes design
  • • Manufacturing risk management
  • • Product reliability management
  • • Production waste management

0.48

TABLE 4.4

Survey Results in Generalizing Proposed Model

Effective factors in generalizing proposed model

Average (ST)

Average (N-ST)

Comprehensiveness

7.55

6.35

Feasibility

8.15

7.45

Flexibility

6.12

5.78

Stability

7.82

6.66

Power

6.75

5.55

Total average (between 1 and 9)

7.28

6.36

Percentage of total averages

80.87

70.64

Success in generalization (between 1 and 9)

7.10

Percentage of success

78.92

ST: Statistical techniques, N-ST: Non-Statistical techniques.

TABLE 4.5

Research Data Reliability

Reliability statistics

Cronbach's

alpha

Cronbach's alpha based on

standardized items

Number of items

0.82

0.825

5

Generalizing the Assessment Results of the Model to Other Organizations

In order to generalize the assessment results of the model, our questionnaires were administered among 26 representative managers of some industries affiliated w'ith the Defense Industries Organization (DIO). The results of this survey are presented in Table 4.4 (see Appendix).

The research reliability values for the 26 management representatives of some industries affiliated w'ith the DIO are presented in Table 4.5.

Assessing the Model’s Risks and Opportunities in Manufacturing Industries

Risks and opportunities management is a continuous process and, if properly implemented, can help keep all constituents of organization in a continuously improving state. Risks and opportunities management is illustrated in Figure 4.3.

Risks and opportunities management process

FIGURE 4.3 Risks and opportunities management process.

4.6.1 Risks and Opportunities Identification

By reviewing a source list of all potential risks and opportunities along with past experiences, the organizational risks and opportunities are identified in all three process categories: main, leadership, and support. The role of risks and opportunities in relation to all three categories of processes is indicated in Figure 4.4.

The following are the risks identified in the main processes (Figure 4.5).

The following are the risks identified the leadership processes (Figure 4.6).

The following are the risks identified in the support processes (Figure 4.7).

4.6.2 Risks and Opportunities Assessment

By using measurement tools, the risks and opportunities should be categorized and prioritized. The number of risks and opportunities usually exceeds the organizational capacity to deploy a specific system to analyze them and design emergency plans. The prioritization process helps organizations to prioritize the risks and opportunities that are more urgent and more likely to occur. It is recommended that risks and opportunities be prioritized by using the data given in Table 3.15.

4.6.3 Responding to Risks and Opportunities

The classic approach for dealing with risks and opportunities is to move from identifying the issue to its depth. However, it must first be determined how risks and

Relationship between risks and opportunities and three categorized processes

FIGURE 4.4 Relationship between risks and opportunities and three categorized processes.

Identified risks in main processes

FIGURE 4.5 Identified risks in main processes.

opportunities can be better managed and the root causes of identified risks and opportunities be recognized. In this regard, the following questions might be asked:

  • • What are the causes of these risks and opportunities?
  • • How can these risks and opportunities affect the organization?

Generally, in responding to risks, the following occurs:

  • • Avoidance: Eliminating a particular risk or threat by removing its cause (preventive action).
  • • Adjustment: Reducing the expected financial value of a particular risk by reducing its occurrence.
Identified risks in leadership processes

FIGURE 4.6 Identified risks in leadership processes.

• Acceptance: Accepting the consequences of the risk, which most often occurs by formulating and implementing an emergency plan for an event that is likely to happen. This emergency plan can be implemented for a short term and will last in the organization for as long as the risk threat continues.

Responding to opportunities generally includes:

• Modification: Exploiting the advantages of the created positive outcomes of that opportunity on a permanent or temporary basis.

Identified risks in support processes

FIGURE 4.7 Identified risks in support processes.

Impacts of Implementing the Model in Industrial Economics

The industrial economics is one of the most important issues studied since the beginning of the 21st century. In a valuable research study, this issue is divided into two categories (Federico, 2016):

• Empirical economics

This includes estimating demand functions as well as cost functions, measuring market pow'er and power assessment of market entrance. It can also include a variety of activities focused on the impact of particular strategies in competitive markets.

• Theoretical economics

This includes assessing different models under different circumstances of application. Generally, this branch of economics deals with simulation processes.

The best quality engineering techniques for both branches of economics are presented in Figure 4.8.

The proposed quality engineering techniques which contain both statistical and non-statistical procedures can help us achieve a better understanding of relevant components in industrial economics. As a matter of fact, these techniques can provide robust tools for decision makers in implementing any short- or long-term plans in economics.

Suggested QET for industrial economics

FIGURE 4.8 Suggested QET for industrial economics.

Exercise

4.1. The results related to the importance and performance of implementing the QET model in a quality management system (QMS), in one industry, are displayed in the table below, (a Likert scale is used from 1 to 9.)

N

Techniques

Average of importance

Variance of importance

Average of performance

Variance of performance

А

Descriptive statistics

6.83

3.24

3.17

2.5

В

Design and analysis of experiments

7.17

2.5

3

2.9

С

Statistical hypothesis tests

5

4.36

2.83

1.8

D

Process capability analysis

7

3.64

3

2.18

Е

Regression analysis

3.83

6.15

2

1.1

F

Reliability analysis

3.67

4.6

2.5

2.27

G

Sampling

6.83

4

3.17

1.8

Н

Simulation

4.17

6.88

2

1.1

I

Statistical process control charts

6.17

3.24

2.83

2.5

J

Statistical tolerances

4.17

4.7

2.33

2.42

К

Time series analysis

5

3.64

2.67

2.06

How can the above table, in both sections including importance and performance, be analyzed?

 
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