An Integrated Lean and Six Sigma Framework for Improving Productivity Performance: A Case Study in a Spanish Chemicals Manufacturer
Abstract
1. Introduction
Literature Review
2. Materials and Methods
2.1. Lean Tools Deployment
2.1.1. Ishikawa Diagram
2.1.2. SIPOC Diagram
2.1.3. Value Stream Map
3. Results and Discussion
3.1. Define
3.2. Measure
Test | D2R kg/L | Y21R kg C21R/kg T | Y22R kg C22R/kg T | Y21T − Y21R kg C21/kg T | Y22T − Y22R kg C22/kg T | D2T − D2R kg/L |
---|---|---|---|---|---|---|
1 | 1.328 | 0.610 | 0.031 | −0.010 | −0.001 | 0.002 |
2 | 1.328 | 0.610 | 0.031 | −0.010 | −0.001 | 0.002 |
3 | 1.332 | 0.603 | 0.032 | −0.003 | −0.002 | −0.002 |
4 | 1.309 | 0.596 | 0.031 | 0.004 | −0.001 | 0.021 |
5 | 1.328 | 0.610 | 0.033 | −0.010 | −0.003 | 0.002 |
6 | 1.324 | 0.599 | 0.030 | 0.001 | 0.000 | 0.006 |
7 | 1.325 | 0.600 | 0.030 | 0.000 | 0.000 | 0.005 |
8 | 1.325 | 0.600 | 0.030 | 0.000 | 0.000 | 0.005 |
9 | 1.328 | 0.600 | 0.030 | 0.000 | 0.000 | 0.002 |
10 | 1.328 | 0.598 | 0.028 | 0.002 | 0.002 | 0.002 |
11 | 1.328 | 0.600 | 0.030 | 0.000 | 0.000 | 0.002 |
12 | 1.330 | 0.598 | 0.030 | 0.002 | 0.000 | 0.000 |
13 | 1.331 | 0.591 | 0.030 | 0.009 | 0.000 | −0.001 |
14 | 1.333 | 0.602 | 0.031 | −0.002 | −0.001 | −0.003 |
15 | 1.331 | 0.582 | 0.030 | 0.018 | 0.000 | −0.001 |
16 | 1.332 | 0.592 | 0.032 | 0.008 | −0.002 | −0.002 |
17 | 1.335 | 0.598 | 0.031 | 0.002 | −0.001 | −0.005 |
18 | 1.330 | 0.593 | 0.028 | 0.007 | 0.002 | 0.000 |
19 | 1.327 | 0.600 | 0.030 | 0.000 | 0.000 | 0.003 |
20 | 1.336 | 0.600 | 0.029 | 0.000 | 0.001 | −0.006 |
21 | 1.320 | 0.595 | 0.025 | 0.005 | 0.005 | 0.010 |
22 | 1.320 | 0.595 | 0.025 | 0.005 | 0.005 | 0.010 |
23 | 1.328 | 0.598 | 0.029 | 0.002 | 0.001 | 0.002 |
24 | 1.327 | 0.600 | 0.028 | 0.000 | 0.002 | 0.003 |
25 | 1.328 | 0.598 | 0.028 | 0.002 | 0.002 | 0.002 |
26 | 1.328 | 0.598 | 0.028 | 0.002 | 0.002 | 0.002 |
27 | 1.327 | 0.598 | 0.030 | 0.002 | 0.000 | 0.003 |
28 | 1.328 | 0.600 | 0.035 | 0.000 | −0.005 | 0.002 |
29 | 1.330 | 0.600 | 0.030 | 0.000 | 0.000 | 0.000 |
30 | 1.332 | 0.595 | 0.030 | 0.005 | 0.000 | −0.002 |
31 | 1.300 | 0.590 | 0.027 | 0.010 | 0.003 | 0.030 |
32 | 1.332 | 0.597 | 0.028 | 0.003 | 0.002 | −0.002 |
33 | 1.332 | 0.596 | 0.028 | 0.004 | 0.002 | −0.002 |
34 | 1.330 | 0.600 | 0.030 | 0.000 | 0.000 | 0.000 |
35 | 1.331 | 0.600 | 0.030 | 0.000 | 0.000 | −0.001 |
Test | D3R kg/L | Y31R kg C31R/kg T | Y31T − Y31R kg C31/kg T | D3T − D3R kg/L |
---|---|---|---|---|
1 | 1.162 | 0.052 | −0.011 | −0.012 |
2 | 1.162 | 0.052 | −0.011 | −0.012 |
3 | 1.163 | 0.051 | −0.010 | −0.013 |
4 | 1.163 | 0.047 | −0.006 | −0.013 |
5 | 1.145 | 0.047 | −0.006 | 0.005 |
6 | 1.145 | 0.045 | −0.004 | 0.005 |
7 | 1.159 | 0.047 | −0.006 | −0.009 |
8 | 1.160 | 0.045 | −0.004 | −0.010 |
9 | 1.160 | 0.047 | −0.006 | −0.010 |
10 | 1.160 | 0.042 | −0.001 | −0.010 |
11 | 1.160 | 0.042 | −0.001 | −0.010 |
12 | 1.145 | 0.039 | 0.002 | 0.005 |
13 | 1.145 | 0.038 | 0.003 | 0.005 |
14 | 1.162 | 0.041 | 0.000 | −0.012 |
15 | 1.142 | 0.044 | −0.003 | 0.008 |
16 | 1.142 | 0.044 | −0.003 | 0.008 |
17 | 1.144 | 0.045 | −0.004 | 0.006 |
18 | 1.144 | 0.045 | −0.004 | 0.006 |
19 | 1.149 | 0.047 | −0.006 | 0.001 |
20 | 1.163 | 0.041 | 0.000 | −0.013 |
21 | 1.161 | 0.047 | −0.006 | −0.011 |
22 | 1.161 | 0.049 | −0.008 | −0.011 |
23 | 1.160 | 0.045 | −0.004 | −0.010 |
24 | 1.145 | 0.045 | −0.004 | 0.005 |
25 | 1.145 | 0.045 | −0.004 | 0.005 |
26 | 1.153 | 0.047 | −0.006 | −0.003 |
27 | 1.160 | 0.048 | −0.007 | −0.010 |
28 | 1.160 | 0.048 | −0.007 | −0.010 |
29 | 1.172 | 0.048 | −0.007 | −0.022 |
30 | 1.173 | 0.050 | −0.009 | −0.023 |
31 | 1.173 | 0.052 | −0.011 | −0.023 |
32 | 1.179 | 0.049 | −0.008 | −0.029 |
33 | 1.157 | 0.046 | −0.005 | −0.007 |
34 | 1.172 | 0.040 | 0.001 | −0.022 |
35 | 1.153 | 0.037 | 0.004 | −0.003 |
3.3. Analyze
3.4. Improve
3.5. Control
Test | D3R’ kg/L | D3T − D3R’ kg/L | Y31R’ kg C31/kg T |
---|---|---|---|
1 | 1.140 | 0.010 | 0.043 |
2 | 1.165 | −0.015 | 0.045 |
3 | 1.150 | 0.000 | 0.044 |
4 | 1.155 | −0.005 | 0.047 |
5 | 1.175 | −0.025 | 0.049 |
6 | 1.160 | −0.010 | 0.047 |
7 | 1.166 | −0.016 | 0.046 |
8 | 1.170 | −0.020 | 0.048 |
9 | 1.152 | −0.002 | 0.044 |
10 | 1.160 | −0.010 | 0.045 |
11 | 1.145 | 0.005 | 0.043 |
12 | 1.150 | 0.000 | 0.044 |
13 | 1.155 | −0.005 | 0.045 |
14 | 1.161 | −0.011 | 0.046 |
15 | 1.160 | −0.010 | 0.045 |
4. Conclusions
Author Contributions
Funding
Institutional Review Board Statement
Data Availability Statement
Conflicts of Interest
References
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Phase | Contents | Application |
---|---|---|
Define | Indicate the main objective of the application, as well as the critical project to be developed | Reducing possible losses of ingredients used in manufacturing. Associated with this are also the purchasing process, the generation of waste, and the use of energy resources |
Measure | Develop a data collection plan and compare data to identify problems and gaps | Analysis of manufactured products. Relationship with the composition of raw materials and the reliability of added quantities |
Analyze | Determine the causes of defects and the sources of variation | Establish relationships between the data obtained through analysis using graphical techniques, statistics, etc. |
Improve | Propose measures to reduce or eliminate variations | Study trends and possible corrective measures to be implemented |
Control | Check that the process variations comply with the established requirements | Determine the impact of the proposed changes on the processes and their follow-up |
Test | D1R kg/L | Y11R kg C11R/kg T | Y11T − Y11R kg C11/kg T | D1T − D1R kg/L |
---|---|---|---|---|
1 | 1.222 | 0.057 | −0.002 | −0.029 |
2 | 1.222 | 0.057 | −0.002 | −0.027 |
3 | 1.226 | 0.051 | 0.004 | −0.019 |
4 | 1.229 | 0.055 | 0.000 | −0.008 |
5 | 1.227 | 0.053 | 0.002 | −0.013 |
6 | 1.219 | 0.054 | 0.001 | −0.029 |
7 | 1.208 | 0.047 | 0.008 | −0.010 |
8 | 1.213 | 0.052 | 0.003 | −0.026 |
9 | 1.229 | 0.051 | 0.004 | −0.026 |
10 | 1.210 | 0.051 | 0.004 | −0.020 |
11 | 1.226 | 0.057 | −0.002 | −0.027 |
12 | 1.226 | 0.056 | −0.001 | −0.030 |
13 | 1.220 | 0.057 | −0.002 | −0.028 |
14 | 1.227 | 0.052 | 0.003 | −0.025 |
15 | 1.230 | 0.052 | 0.003 | −0.012 |
16 | 1.228 | 0.052 | 0.003 | −0.014 |
17 | 1.225 | 0.055 | 0.000 | −0.030 |
18 | 1.212 | 0.055 | 0.000 | −0.032 |
19 | 1.214 | 0.052 | 0.003 | −0.017 |
20 | 1.230 | 0.051 | 0.004 | −0.026 |
21 | 1.232 | 0.051 | 0.004 | −0.033 |
22 | 1.217 | 0.054 | 0.001 | −0.012 |
23 | 1.226 | 0.052 | 0.003 | −0.012 |
24 | 1.233 | 0.057 | −0.002 | −0.034 |
25 | 1.212 | 0.051 | 0.004 | −0.019 |
26 | 1.212 | 0.052 | 0.003 | −0.026 |
27 | 1.234 | 0.053 | 0.002 | −0.020 |
28 | 1.219 | 0.054 | 0.001 | −0.027 |
29 | 1.226 | 0.053 | 0.002 | −0.011 |
30 | 1.220 | 0.053 | 0.002 | −0.031 |
31 | 1.227 | 0.057 | −0.002 | −0.018 |
32 | 1.211 | 0.057 | −0.002 | −0.018 |
33 | 1.231 | 0.057 | −0.002 | −0.029 |
34 | 1.218 | 0.057 | −0.002 | −0.027 |
35 | 1.218 | 0.051 | 0.004 | −0.019 |
Pi | x | Δx (%) | LI | ΔLI (%) | LS | ΔLS (%) | σ |
---|---|---|---|---|---|---|---|
D1R | 1.222 | 1.83 | 1.208 | 0.67 | 1.234 | 2.83 | 0.007 |
Y11R | 0.054 | −1.82 | 0.047 | −14.55 | 0.057 | 3.64 | 0.002 |
D2R | 1.327 | −0.23 | 1.300 | −2.26 | 1.336 | 0.45 | 0.007 |
Y21R | 0.598 | −0.33 | 0.582 | −3.00 | 0.610 | 1.67 | 0.005 |
Y22R | 0.030 | 0.00 | 0.025 | −16.67 | 0.035 | 16.67 | 0.002 |
D3R | 1.157 | 0.61 | 1.142 | −0.70 | 1.179 | 2.52 | 0.010 |
Y31R | 0.046 | 12.20 | 0.037 | −9.75 | 0.052 | 26.83 | 0.004 |
Pi | PT L | kg/L | ΔPT kg | kg CijR/kg T | ΔYij kg CijR/kg T | ΔMPij kg |
---|---|---|---|---|---|---|
P1 | 193,440 | −0.022 | −4255.68 | 0.054 | −229.81 | −919.23 |
P2 | 72,160 | 0.003 | 216.48 | 0.598 0.030 | 129.46 6.49 | 199.16 25.98 |
P3 | 130,080 | −0.007 | −910.56 | 0.046 | −41.89 | −598.43 |
Loss estimation P1, kg | −2127.84 |
Average value (D1T − D1R), kg/L | −0.011 |
Estimated average value D1R, kg/L | 1.211 |
Variation of D1R over D1T, % | 0.92 |
Loss estimation MP11, kg | −468.97 |
Loss estimation Y11, kg C11/kg tot | −114.91 |
Loss estimation P3, kg | −459.62 |
Average value (D3T − D3R), kg/L | −0.004 |
Estimated average value D3R, kg/L | 1.154 |
Variation of D3R over D3T, % | 0.35 |
Loss estimation MP31, kg | −299.22 |
Loss estimation Y31, kg C31/kg tot | −20.95 |
Category | Causes | Action | Involved | Result/Cost | Time |
---|---|---|---|---|---|
Methods | Production programming | MP production and procurement plan Demand for updated sales forecasts | Planning and Purchasing Commercial | Gant diagrams. ERP adaptationCRM EUR 5000 | 3–6 months |
Standardization manufacturing procedures | Specific working instructions | Production | Detailed working procedure | 2 months | |
Facilities | Equipment availability | Specific preventive maintenance plan | Maintenance | Technical services MES 4500 € | 3–6 months |
Timetable with prioritization of productions | Production | Production program | - | ||
Staff | Appropriate staff training | Training on product handling and time management | Human Resources | Training program EUR 3000 | 1 week |
Precise raw materials handling | Training in handling measuring equipment | Production and Human Resources | Training program EUR 1500 | 1 week | |
Environment | Workspace layout | Elimination of obstacles Tidiness of the work area | Production Production | Reorganization of spaces Good practices | 1 week |
Delimit a suitable and specific area for raw materials | Raw materials location área Regular audits | Maintenance | Signaling and use of beacons EUR 200 | 2 weeks | |
Materials | Reduce variability of raw materials composition | Choice of raw materials whose variability in composition is <2% | Purchasing | Search for three suppliers and choose one with the least variability in composition | 1–2 months |
Measurement | Verification of measurement equipment | Establish a program for the adjustment and calibration of measuring equipment | Quality | Entity official verification EUR 500 | 1 month |
Test | D1R’ kg/L | D1T − D1R’ kg/L | Y11R’ kg C11/kg T |
---|---|---|---|
1 | 1.200 | 0.000 | 0.049 |
2 | 1.215 | −0.015 | 0.053 |
3 | 1.220 | −0.020 | 0.054 |
4 | 1.199 | 0.001 | 0.051 |
5 | 1.196 | 0.004 | 0.050 |
6 | 1.215 | −0.015 | 0.052 |
7 | 1.225 | −0.025 | 0.053 |
8 | 1.210 | −0.010 | 0.051 |
9 | 1.220 | −0.020 | 0.053 |
10 | 1.215 | −0.015 | 0.053 |
11 | 1.195 | 0.005 | 0.050 |
12 | 1.198 | 0.002 | 0.051 |
13 | 1.200 | 0.000 | 0.050 |
14 | 1.212 | −0.012 | 0.052 |
15 | 1.210 | −0.010 | 0.052 |
P1 | P3 | ||
---|---|---|---|
D1R* kg/L | Y11R* kg C11/kg T | D3R* kg/L | Y31R* kg C31/kg T |
1.211 | 0.054 | 1.158 | 0.057 |
1.211 | 0.055 | 1.158 | 0.057 |
1.215 | 0.054 | 1.159 | 0.056 |
1.218 | 0.056 | 1.159 | 0.052 |
1.216 | 0.056 | 1.141 | 0.052 |
1.208 | 0.050 | 1.141 | 0.050 |
1.197 | 0.054 | 1.155 | 0.052 |
1.202 | 0.052 | 1.156 | 0.050 |
1.218 | 0.053 | 1.156 | 0.052 |
1.199 | 0.046 | 1.156 | 0.047 |
1.215 | 0.051 | 1.156 | 0.047 |
1.215 | 0.050 | 1.141 | 0.044 |
1.209 | 0.050 | 1.141 | 0.043 |
1.216 | 0.056 | 1.158 | 0.046 |
1.219 | 0.055 | 1.138 | 0.049 |
1.217 | 0.056 | 1.138 | 0.049 |
1.214 | 0.051 | 1.140 | 0.050 |
1.201 | 0.051 | 1.140 | 0.050 |
1.203 | 0.051 | 1.145 | 0.052 |
1.219 | 0.054 | 1.159 | 0.046 |
1.221 | 0.054 | 1.157 | 0.052 |
1.206 | 0.051 | 1.157 | 0.054 |
1.215 | 0.050 | 1.156 | 0.050 |
1.222 | 0.050 | 1.141 | 0.050 |
1.201 | 0.053 | 1.141 | 0.050 |
1.201 | 0.051 | 1.149 | 0.052 |
1.223 | 0.056 | 1.156 | 0.053 |
1.208 | 0.050 | 1.156 | 0.053 |
1.215 | 0.051 | 1.168 | 0.053 |
1.209 | 0.052 | 1.169 | 0.055 |
1.216 | 0.053 | 1.169 | 0.057 |
1.200 | 0.052 | 1.175 | 0.054 |
1.220 | 0.052 | 1.153 | 0.051 |
1.207 | 0.056 | 1.168 | 0.045 |
1.207 | 0.056 | 1.149 | 0.042 |
1.211 | 0.054 | 1.158 | 0.057 |
D1R* | Y11R* | D1R’ | Y11R’ | D3R* | Y31R* | D3R’ | Y31R’ | |
---|---|---|---|---|---|---|---|---|
UL | 1.223 | 0.056 | 1.225 | 0.054 | 1.175 | 0.057 | 1.175 | 0.049 |
LL | 1.197 | 0.046 | 1.195 | 0.049 | 1.138 | 0.042 | 1.140 | 0.043 |
x | 1.211 | 0.053 | 1.209 | 0.052 | 1.153 | 0.051 | 1.158 | 0.045 |
σ | 0.007 | 0.002 | 0.010 | 0.001 | 0.010 | 0.004 | 0.009 | 0.002 |
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Alarcón, F.J.; Calero, M.; Martín-Lara, M.Á.; Pérez-Huertas, S. An Integrated Lean and Six Sigma Framework for Improving Productivity Performance: A Case Study in a Spanish Chemicals Manufacturer. Appl. Sci. 2024, 14, 10894. https://doi.org/10.3390/app142310894
Alarcón FJ, Calero M, Martín-Lara MÁ, Pérez-Huertas S. An Integrated Lean and Six Sigma Framework for Improving Productivity Performance: A Case Study in a Spanish Chemicals Manufacturer. Applied Sciences. 2024; 14(23):10894. https://doi.org/10.3390/app142310894
Chicago/Turabian StyleAlarcón, Francisco J., Mónica Calero, María Ángeles Martín-Lara, and Salvador Pérez-Huertas. 2024. "An Integrated Lean and Six Sigma Framework for Improving Productivity Performance: A Case Study in a Spanish Chemicals Manufacturer" Applied Sciences 14, no. 23: 10894. https://doi.org/10.3390/app142310894
APA StyleAlarcón, F. J., Calero, M., Martín-Lara, M. Á., & Pérez-Huertas, S. (2024). An Integrated Lean and Six Sigma Framework for Improving Productivity Performance: A Case Study in a Spanish Chemicals Manufacturer. Applied Sciences, 14(23), 10894. https://doi.org/10.3390/app142310894