# The Effect of SMED on Benefits Gained in Maquiladora Industry

^{1}

^{2}

^{3}

^{*}

## Abstract

**:**

## 1. Introduction

#### 1.1. Stages of SMED

- Is a statistical analysis performed to know time variability of the process [11]?
- Is a statistical analysis performed to know the average process time [11]?
- Is there a detailed analysis of the possible causes of time variability in the process [11]?
- Are operators’ activities being measured with a chronometer [12]?
- Has the company identified activities related to changeovers [14]?

- Detect basic problems that are part of the work routine [17].

- Is the previous work completed before starting changeover [17]?
- Are visual marks used instead of making trial and error adjustments to calibrations [18]?
- Have steps related to search of tools, raw materials, and products been eliminated [18]?
- Have activities been reexamined to make sure none of them has been wrongly assumed as being internal [19]?

- Reexamine operations to see whether any activities are wrongly assumed as being internal.
- Find the way to convert these activities into external setup.

- Train operators to maintain improvement in process time [21].

#### 1.2. SMED Benefits

#### 1.3. Research Problem and Objective

#### 1.4. Hypotheses

**H**

_{1}:**H**

_{2}:**H**

_{3}:**H**

_{4}:**H**

_{5}:**H**

_{6}:## 2. Methodology

#### 2.1. Survey Design

#### 2.2. Data Collection

#### 2.3. Data Capture and Screening

^{®}(IBM, Armonk, New York, USA). Each arrow of the database corresponded to an administered survey (case), while each column included one of the 22 items integrating the five latent variables. Then, data were screened to identify missing values and outliers.

#### 2.4. Survey Validation

#### 2.5. Structural Equation Model

^{®}algorithm with a resampling bootstrap in order to improve values of indices and diminish the effect of possible outliers [62]. In addition, hypotheses were validated by analyzing direct, indirect, and total effects between latent variables. As for direct effects, we estimated values of the beta parameter as a dependency measure, while p-values were used to determine statistical significance of hypotheses. Since statistical tests were run with 95% of confidence level, p-values had to be lower than 0.05. On the other hand, indirect effects between latent variables occurred through a third our fourth latent variable, also known as mediator. Indirect effects are depicted in the model by more than two paths. Finally, to obtain total effects between latent variables, we added their direct and indirect effects.

## 3. Results

#### 3.1. Description of the Sample

#### 3.2. Statistical Validation of the Survey

#### 3.3. Structural Equation Model

#### 3.3.1. Direct Effects

^{2}value, indicating the amount of variance explained by independent latent variables. Since all R

^{2}values are lower than one, it means that other variables (not included in this model) also affect that dependent latent variable. In this model, two latent variables (Separation Phase and Transformation Phase) are affected by one independent latent variable, and two more (Improvement Phase and Benefits) are influenced by two independent latent variables.

**H**

_{1}:**H**

_{2}:**H**

_{3}:**H**

_{4}:**H**

_{5}:**H**

_{6}:#### 3.3.2. Size of Direct Effects

^{2}value, which must be decomposed in the number of independent latent variables that explain a dependent latent variable. For instance, Separation Phase is 43% explained by Identification Phase, while the remaining 57% may come from other activities, such as the 5S.

#### 3.3.3. Indirect Effects

#### 3.3.4. Total Effects

## 4. Conclusions

- (1)
- Before implementing SMED in their processes, companies must have adequate information regarding their processes, since activities performed at the Identification Phase have a strong effect on activities at Separation Phase. Thus, information at the Identification Phase is the basis for SMED success.
- (2)
- Companies must pay attention to SMED activities carried out during the Separation Phase, since proper identification of internal and external activities has direct and positive effects on activities performed at the Transformation Phase and the Improvement Phase. Therefore, the planning stage is key to SMED success, since it helps effectively identify internal and external activities and convert many internal activities into external ones. As a result, machines performance is maximized.
- (3)
- Activities carried out at the Transformation Phase and Improvement Phase are key to obtaining the expected SMED Benefits, since these variables explain up to 48% of them. Transformation Phase is responsible for 27.5%, while Improvement Phase explains 20.2%.
- (4)
- As a LM tool, SMED is extremely useful for the maquiladora industry, since in the manufacturing industry changeovers are recurrent and must be reduced in time.
- (5)
- In this research, we identified many activities required for SMED implementation and several SMED benefits. However, results from the validation process of latent variables showed that not all of these activities or benefits were relevant. Consequently, some of them were removed from the structural equation model.
- (6)
- Based on the highest values of combined loadings shown in Table 3, the most important activity at SMED Identification Phase is the use of a statistical analysis to know time variability of the process. The importance of this activity is supported by the fact that companies must always have at hand empirical evidence on the production process before launching any improvement strategy. As for Separation Phase, results show that the most important activity refers to listing the main sequential setup operations to identify external operations. In other words, with SMED most activities must be performed while the machine is running, thereby saving time wasted during stoppages.
- (7)
- As regards the Transformation Phase, values of combined loadings show that the most important activity is to reevaluate the list made at the Separation Phase to make sure that internal or external activities have been correctly classified. In fact, it is important to clearly identify every activity and assess whether it can be executed while the machine is working. Finally, both activities analyzed at the Improvement Phase showed the same combined loading value, thereby indicating that they are of equal importance.
- (8)
- Finally, as regards Benefits gained from SMED implementation, it seems that setup time improvement is the most important to Mexican manufacturing companies, since it shows the highest value. In fact, improving setup times is the major purpose of and justification for a SMED implementation program.

## 5. Future Research

## Author Contributions

## Conflicts of Interest

## Appendix A. SMED Questionnaire

1 | 2 | 3 | 4 | 5 |

Never | Rarely | Often | Very frequently | Always |

Seniority (years) ▯ 0–1 ▯ 1–2 ▯ 2–5 ▯ 5–10 ▯ More than 10 |

Industrial sector ▯ Machining ▯ Electrical ▯ Automotive ▯ Aeronautics ▯ Electronics ▯ Logistics ▯ Other ______ |

Gender ▯ Female ▯ Male |

Position ▯ Manager ▯ Engineer ▯ Supervisor ▯ Technical ▯ Operator |

## Preliminary Stage 0: Changeover Activities

**Were the following steps completed before implementing SMED?**

1 | 2 | 3 | 4 | 5 | |

S0 01 5 s techniques? | |||||

S0 02 Is a statistical analysis performed to know time variability of the process? | |||||

S0 03 Is there a statistical analysis to know the average process time | |||||

S0 04 Is there a detailed analysis of the possible causes of time variability in the process? | |||||

S0 05 Have operators been interviewed about processes and the machines that they operate? | |||||

S0 06 Are operators’ activities being measured with a chronometer? | |||||

S0 07 Is there a video recording of process? | |||||

S0 08 Were photographs taken of the process? | |||||

S0 09 Is it necessary to talk to staff to determine any conditions that do not add value? |

## First Stage: Separate Internal and External Activities

**Were the following steps completed?**

1 | 2 | 3 | 4 | 5 | |

S1 01 List the main sequential setup operations to identify internal activities | |||||

S1 02 List the main sequential setup operations to identify external activities | |||||

S1 03 Detect basic problems that are part of the work routine. | |||||

S1 04 Is setup of tools, parts and supplies carried out while machines are running? |

## Second Stage: Turn Internal Work into External

1 | 2 | 3 | 4 | 5 | |

S2 01 Is previous work completed before starting changeover? | |||||

S2 02 Are visual marks used instead of making trial and error adjustments to calibrations? | |||||

S2 03 Have steps related to the search of tools, raw materials, and products been eliminated? | |||||

S2 04 Have activities been reexamined to make sure none of them has been wrongly assumed as being internal? |

## Third Stage: Streamlining all aspects of setup and systematic improvement of all operations

1 | 2 | 3 | 4 | 5 | |

S3 01 Have key setup activities been recorded to help improve process time? | |||||

S3 02 Have operators been trained to maintain process improvement? |

## SMED Benefits

**Were the following benefits obtained?**

1 | 2 | 3 | 4 | 5 | |

BE 01 Increased productivity | |||||

BE 02 It eliminates stocks fail due to errors in estimating demand | |||||

BE 03 Less product deterioration | |||||

BE 04 Increased work rates and production capacity of machines | |||||

BE 05 Fewer or no errors in machines setup | |||||

BE 06 Improved product quality | |||||

BE 07 Increased security in operations | |||||

BE 08 Improved setup times | |||||

BE 09 Reduced lot size costs | |||||

BE 10 Improved operators attitude | |||||

BE 11 Lower training level | |||||

BE 12 Reduced lead times | |||||

BE 13 No waiting times | |||||

BE 14 Small batch production | |||||

BE 15 Flow production | |||||

BE 16 Increased production flexibility | |||||

BE 17 Reduction of setup time into productive time | |||||

BE 18 Reduced inventory levels | |||||

BE 19 Reduced lot production size | |||||

BE 20 Production flow | |||||

BE 21 Reduced bottlenecks | |||||

BE 22 Reduced in process inventory | |||||

BE 23 Quick answer to customer needs | |||||

BE 24 Increased ability to adapt to changing demands | |||||

BE 25 Increased machine utilization rate |

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**Figure 1.**Representation of changeover time [8].

**Figure 2.**SMED conceptual stages and practical techniques [7]

Scale | Description |
---|---|

1 | Never |

2 | Rarely |

3 | Often |

4 | Very frequently |

5 | Always |

Index | Identification Phase | Separation Phase | Transformation Phase | Improvement Phase | Benefits |
---|---|---|---|---|---|

R-squared | 0.427 | 0.388 | 0.365 | 0.476 | |

Adj. R-squared | 0.426 | 0.386 | 0.361 | 0.474 | |

Composite reliability | 0.897 | 0.916 | 0.868 | 0.845 | 0.914 |

Cronbach’s alpha | 0.855 | 0.861 | 0.797 | 0.634 | 0.892 |

Avg. Var. Extract. (AVE) | 0.637 | 0.784 | 0.622 | 0.732 | 0.571 |

Full collin. VIF | 2.045 | 2.246 | 2.021 | 1.746 | 2.151 |

Q-squared | 0.428 | 0.389 | 0.365 | 0.478 |

Item | Identification Phase | Separation Phase | Transformation Phase | Improvement Phase | Benefits | p Value |
---|---|---|---|---|---|---|

S0 02 | 0.857 | 0.060 | −0.006 | −0.079 | −0.036 | <0.001 |

S0 03 | 0.851 | 0.045 | −0.050 | −0.090 | 0.092 | <0.001 |

S0 04 | 0.824 | 0.087 | −0.050 | −0.078 | 0.140 | <0.001 |

S0 05 | 0.716 | −0.190 | 0.177 | 0.159 | −0.083 | <0.001 |

S0 06 | 0.731 | −0.035 | −0.052 | 0.131 | −0.141 | <0.001 |

S1 01 | 0.069 | 0.920 | −0.107 | −0.015 | 0.059 | <0.001 |

S1 02 | −0.036 | 0.924 | −0.031 | −0.040 | −0.002 | <0.001 |

S1 03 | −0.038 | 0.808 | 0.157 | 0.064 | −0.065 | <0.001 |

S2 01 | 0.000 | 0.203 | 0.776 | −0.152 | 0.062 | <0.001 |

S2 02 | −0.112 | 0.067 | 0.790 | −0.037 | −0.005 | <0.001 |

S2 03 | 0.109 | −0.228 | 0.767 | 0.095 | −0.071 | <0.001 |

S2 04 | 0.006 | −0.043 | 0.821 | 0.090 | 0.013 | <0.001 |

S3 01 | 0.084 | −0.095 | −0.002 | 0.856 | −0.116 | <0.001 |

S3 02 | −0.084 | 0.095 | 0.002 | 0.856 | 0.116 | <0.001 |

BE 01 | −0.073 | 0.150 | −0.037 | 0.194 | 0.754 | <0.001 |

BE 02 | 0.150 | −0.121 | 0.189 | 0.029 | 0.696 | <0.001 |

BE 04 | 0.192 | −0.089 | 0.022 | −0.061 | 0.765 | <0.001 |

BE 05 | −0.089 | 0.111 | 0.033 | −0.115 | 0.779 | <0.001 |

BE 06 | −0.027 | −0.171 | −0.092 | −0.03 | 0.783 | <0.001 |

BE 07 | −0.144 | −0.002 | −0.042 | 0.039 | 0.727 | <0.001 |

BE 08 | −0.076 | 0.112 | −0.040 | −0.017 | 0.822 | <0.001 |

BE 09 | 0.087 | −0.007 | −0.016 | −0.030 | 0.714 | <0.001 |

Index | Value |
---|---|

Average path coefficient (APC) | 0.456, p < 0.001 |

Average R-squared (ARS) | 0.414, p < 0.001 |

Average adjusted R-squared (AARS) | 0.412, p < 0.001 |

Average block VIF (AVIF) acceptable if ≤5, ideally ≤3.3 | 1.499 |

Average full collinearity VIF (AFVIF) acceptable if ≤5, ideally ≤3.3 | 2.042 |

Tenenhaus GoF (GoF) small ≥0.1, medium ≥0.25, large ≥0.36 | 0.526 |

Identification Phase | Separation Phase | Transformation Phase | |
---|---|---|---|

Transformation Phase | 0.407 (p < 0.001) | ||

ES = 0.235 | |||

Improvement Phase | 0.358 (p < 0.001) | 0.207 (p < 0.001) | |

ES = 0.190 | ES = 0.113 | ||

Benefits | 0.303 (p < 0.001) | 0.463 (p < 0.001) | 0.115 (p < 0.001) |

ES = 0.177 | ES = 0.288 | ES = 0.072 |

Identification Phase | Separation Phase | Transformation Phase | Improvement Phase | |
---|---|---|---|---|

Separation Phase | 0.654 (p < 0.001) | |||

ES = 0.427 | ||||

Transformation Phase | 0.407 (p < 0.001) | 0.623 (p < 0.001) | ||

ES = 0.235 | ES = 0.388 | |||

Transformation Phase | 0.358 (p < 0.001) | 0.547 (p < 0.001) | 0.333 (p < 0.001) | |

ES = 0.190 | ES = 0.298 | ES = 0.180 | ||

Benefits | 0.303 (p < 0.001) | 0.463 (p < 0.001) | 0.555 (p < 0.001) | 0.347 (p < 0.001) |

ES = 0.177 | ES = 0.288 | ES = 0.347 | ES = 0.202 |

© 2016 by the authors; licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC-BY) license (http://creativecommons.org/licenses/by/4.0/).

## Share and Cite

**MDPI and ACS Style**

Díaz-Reza, J.R.; García-Alcaraz, J.L.; Martínez-Loya, V.; Blanco-Fernández, J.; Jiménez-Macías, E.; Avelar-Sosa, L.
The Effect of SMED on Benefits Gained in Maquiladora Industry. *Sustainability* **2016**, *8*, 1237.
https://doi.org/10.3390/su8121237

**AMA Style**

Díaz-Reza JR, García-Alcaraz JL, Martínez-Loya V, Blanco-Fernández J, Jiménez-Macías E, Avelar-Sosa L.
The Effect of SMED on Benefits Gained in Maquiladora Industry. *Sustainability*. 2016; 8(12):1237.
https://doi.org/10.3390/su8121237

**Chicago/Turabian Style**

Díaz-Reza, José Roberto, Jorge Luis García-Alcaraz, Valeria Martínez-Loya, Julio Blanco-Fernández, Emilio Jiménez-Macías, and Liliana Avelar-Sosa.
2016. "The Effect of SMED on Benefits Gained in Maquiladora Industry" *Sustainability* 8, no. 12: 1237.
https://doi.org/10.3390/su8121237