Sedanur Birincioğlu
Chemist – ADCO PETROLEUM ADDITIVES/ Technical Sales and Marketing Specialist
The chemical industry is in a continuous process of innovation and development due to constantly evolving technological demands and tightening environmental regulations. However, this innovation process brings challenges such as complex chemical components and processes as well as high costs and time pressure. This situation causes R&D teams to need more effective and efficient working methods. This situation is similar in the lubricant industry. In this article, I would like to talk about a methodology that R&D teams can use in new product development processes or product improvements: Design of Experiment (DoE).
Design of Experiment (DoE)
Design of Experiment (DoE) is a methodology used to understand how variables affect a process. In the chemical industry, this method plays a critical role in optimizing production processes and improving product quality. DoE aims to determine how the parameters of a process or system should be adjusted and to understand how these parameters interact with each other. Especially in the lubricant industry, DoE is a fundamental tool for new product development and improvement of existing products.
Advantages of DoE
- Efficiency and cost effectiveness: DoE enables efficient and cost-effective experiments by evaluating multiple variables simultaneously. This provides a major advantage in optimizing lubricant formulations and new product development.
- Risk mitigation: In new product development, a systematic understanding of the effects of different component combinations has an important role in reducing risks.
- Improvement of decision-making processes: By identifying the most effective factors, it enables more deliberate decision-making processes.
DoE applications and their effects on lubricant industry
- Product development: A critical tool in the development of new lubricant formulations to determine optimal blends.
- Quality control and testing processes: To test the performance of lubricants, DoE is an effective tool to evaluate product quality under different conditions.
- Impacts on marketing and sales: An effective DoE implementation helps the product gain a competitive advantage in the market. Higher quality and cost-effective products contribute to strengthening marketing and sales strategies.
Design of Experiments (DoE) is defined as the strategy of planning the experiments to be conducted in order to obtain the maximum amount of information from the collected experimental data in an effective manner. Minitab, a statistical program, is widely used in DoE applications and quickly and efficiently analyses and transforms data into information.
The correct use of this information contributes significantly to the easy solution of the most challenging problems. For more than 40 years, Minitab, which has attracted great interest from professionals, is constantly updated and meets the expectations of companies and R&D centers at the maximum level.
Minitab
Minitab is a software programme for statistical data analysis and quality control. This programme is widely used in statistical applications such as quality control, design of experiments, data analysis, regression analysis, accuracy testing and similar statistical applications, especially in industrial and business processes. Minitab is a tool that simplifies statistical and analytical tools and helps users to analyze data effectively.
The prominent features of Minitab are as follows:
Graphics and visualization: Allows you to visualize your data with graphics. This helps you better understand patterns and trends in data sets.
Hypothesis testing: It allows you to perform statistical hypothesis tests and interpret the results.
Regression analysis: Provides regression analysis tools to analyze relationships between dependent and independent variables.
Design of experiments: Statistical design of experiments helps you perform analyses and understand factor interactions for process improvement.
Quality control: Provides quality control with statistical process control graphics and analyses.
Accuracy tests: You can perform accuracy tests for normal distribution, homogeneity of variance and other properties in data sets.
Minitab is a tool that is used especially in line with Six Sigma and similar quality management methodologies. It has a user-friendly interface that makes it easy for even non-expert users in statistics and data analysis to understand and interpret data.
DoE is a powerful tool for the development of innovative solutions in the lubricant industry, as it is used in many fields. The use of software such as Minitab facilitates this process, resulting in faster and more effective results. In addition, the application of this methodology scientifically supports every step of your study.
Case Study:
How to plan an experiment for the selection of an engine oil pour point depressant using the DoE method?
Let us perform an experimental planning that evaluates the influence of factors on the choice of pour point depressant to establish the optimum experimental formulation. This process allows us to understand how the engine oil will affect the desired performance characteristics.
Identification of factors: Pour point depressant concentration (%)
Type of pour point depressant used
Base oil type (Mineral, PAO, Group 3)
Blending time (hours)
Temperature (0C)
Determination of levels:
For pour point depressant concentration: (0,01%, 0,02%, 0,05% , 0,1%)
For the type of pour point depressant used (Evonik Viscoplex 1-260 , Evonik Viscoplex 1-330, Evonik Viscoplex 1-180)
Base oil type: Mineral, PAO, Group 3
For blending time: 1 hour, 3 hours, 5 hours Temperature: 30 0C , 50 0C, 70 0C
Pour point test (ASTM D97)
Design of Experiment: Factors and levels are recorded in Minitab.
Determining the number of experiments: Depending on the number of factors and the number of levels, we will determine the number of experimental rows.
Execution of experiments: The experiments for which the program is created are carried out in sequence, if possible by the same person. Planned analyses are performed and recorded in the program data.
Analysis of data: Statistical methods will be used to analyze the results of the experiment. This allows us to evaluate the influence of factors on the choice of pour point depressant.
By following these steps, the optimum experimental formulation for engine oil pour point depressant selection is established. The results of these experiments allow us to evaluate how the engine oil will affect the desired performance characteristics.
