Ink product quality is influenced by five factors: people, machines, materials, environment, and methods. Four of these 鈥?people, machines, environment, and methods 鈥?can be managed and improved through internal controls. But “materials” is the one factor that sits in the supplier’s hands, and raw material quality directly determines ink product quality.
The ink production process is relatively straightforward. Once a formulation is locked in by the lab, product quality stability depends heavily on the consistency of incoming raw materials. Most ink manufacturers use supplier-provided raw materials directly, without any pre-processing. This makes raw material consistency absolutely critical.
Effectively managing and controlling raw material suppliers is a day-to-day challenge for ink producers. A solid supplier evaluation system is one of the most effective ways to ensure stable incoming material quality. This article uses statistical process control techniques 鈥?collecting and analyzing viscosity test data for a key resin raw material 鈥?to assess the quality assurance capability of different suppliers, providing a data-driven basis for supplier selection and management.
Testing Equipment and Conditions
Instruments and equipment:
- XND1 Flow Cup #4
- Water bath
- 0鈥?00掳C mercury thermometer
- Stopwatch
- JB50-J electric stirrer
- SL1021 electronic balance
- GXX-DH300-II electric constant-temperature drying oven
Test conditions: 25掳C ambient temperature, dissolved to a 20% resin solution.
Suppliers, Raw Material, and Characteristic Index
Suppliers: Three regular suppliers from the past two years, designated as Supplier A, Supplier B, and Supplier C.
Raw material: One specific grade of solid resin.
Characteristic index 鈥?viscosity: The molecular weight of the resin can be inferred from the viscosity of a resin solution at a given concentration. Fluctuations in molecular weight directly reflect the supplier’s production process capability. By statistically analyzing viscosity data, we can gauge production stability. Larger standard deviation means less stable production; smaller standard deviation means more stable production and, by extension, more consistent product quality. Viscosity was therefore selected as the characteristic quality index.
Data Collection and Analysis Method
Resin viscosity inspection data was collected across 2013 and 2014. For each supplier, ten batches of test data were randomly selected per year. Standard deviation and range were calculated to quantify raw material quality fluctuation for each supplier.
Data Analysis 鈥?2013
Using the standard deviation formula with n=10 samples per supplier:
| Supplier | 危(Xi/10)虏 | 危Xi/10 | Standard Deviation (S) | Range (R) | Xmax | Xmin |
|---|---|---|---|---|---|---|
| A | 970.40 | 95.9 | 23.76 | 62 | 122 | 60 |
| B | 1069.01 | 101.3 | 21.82 | 75 | 135 | 60 |
| C | 645.37 | 79.9 | 9.98 | 30 | 90 | 60 |
2013 conclusion: Supplier C showed the best stability with the smallest standard deviation (9.98) and range (30). Both Supplier A and Supplier B had unsatisfactory production stability. The recommendation was to maximize procurement from Supplier C while requiring corrective action from A and B.
Supplier quality stability ranking: C > A > B
Data Analysis 鈥?2014
| Supplier | 危(Xi/10)虏 | 危Xi/10 | Standard Deviation (S) | Range (R) | Xmax | Xmin |
|---|---|---|---|---|---|---|
| A | 505.68 | 70.2 | 11.29 | 36 | 96 | 60 |
| B | 823.54 | 89.4 | 16.43 | 47 | 114 | 67 |
| C | 748.40 | 86.2 | 7.71 | 28 | 98 | 70 |
2014 conclusion: Supplier C once again ranked best with the smallest standard deviation (7.71) and range (28), confirming the strongest production process control. Supplier A ranked second, and Supplier B remained the poorest performer.
Supplier quality stability ranking: C > A > B
Year-over-Year Trend
Comparing the two years of data, all three suppliers reduced their resin viscosity standard deviation from 2013 to 2014. This indicates that each supplier improved their production control during this period 鈥?exactly the outcome a buyer wants to see.
Conclusions
This statistical analysis clearly establishes the quality assurance capability ranking for this solid resin: Supplier C leads, followed by Supplier A, with Supplier B trailing.
The data also serves as a foundation for ink formulation decisions. By understanding the quality profile of resin from each supplier, ink manufacturers can adjust formulations to match different product grades and customer requirements. A resin with tighter viscosity control goes into premium ink lines; material with wider variation gets directed to less demanding applications 鈥?or the supplier gets phased out.
On the procurement side, statistical supplier analysis provides objective criteria for purchase allocation: increase the share from high-capability suppliers, reduce or eliminate low-capability ones, and issue targeted corrective action requests backed by data.
While the ink production process itself may be relatively simple, maintaining consistent product quality requires solid internal management and stable raw materials as the foundation. Periodic statistical analysis of supplier raw material characteristics 鈥?combined with other evaluation criteria like on-time delivery and service quality 鈥?creates an effective supplier evaluation system that ensures raw material stability for ink manufacturing.
References
- Wikipedia: Statistical Process Control (SPC) 鈥?Foundational methodology for using statistical techniques to monitor and control production processes
- Wikipedia: Standard Deviation 鈥?Mathematical definition and interpretation of standard deviation as a measure of process variability
- ISO 9001:2015 鈥?Quality Management Systems: International standard for quality management including supplier evaluation requirements
- ASTM D4212 鈥?Viscosity by Dip-Type Viscosity Cups: Standard test method for viscosity using flow cups including the #4 cup
- Wikipedia: Viscosity 鈥?Physical chemistry of viscosity and its relationship to molecular weight in polymer solutions