This paper aims at improving the performance of the tableting process using statistical quality control and fuzzy goal programming. The tableting process was studied. Statistical control tools were used to characterize the existing process for three critical responses including the averages of a tablet’s weight, hardness, and thickness. At initial process factor settings, the estimated process capability index values for the tablet’s averages of weight, hardness, and thickness were 0.58, 3.36, and 0.88, respectively. The L9 array was utilized to provide experimentation design. Fuzzy goal programming was then employed to find the combination of optimal factor settings. Optimization results showed that the process capability index values for ...
We previously determined “Tableting properties” by using a multi-functional single-punch tablet pres...
This study illustrates the application of experimental design and multivariate data analysis in defi...
We developed a new machine learning-based method in order to facilitate the manufacturing processes ...
This paper aims at improving the performance of the tableting process using statistical quality cont...
Optimizing tablets ’ quality with multiple responses using fuzzy goal programming Abbas Al-Refaie1, ...
This case study discusses the use of statistical process control (SPC) for evaluating tablet compres...
Optimizing processing conditions to achieve a critical quality attribute (CQA) is an integral part o...
Context: Tableting is a complex process due to the large number of process parameters that can be va...
This study optimized the performance of plastic extrusion process of drip irrigation pipes using fuz...
To have effective production planning, it is necessary to control the quality of processes. This pap...
In this study, an empirical predictive model was developed based on the quantitative relationships b...
Despite the high quantities of tablets produced daily, many tableting processes are still operated a...
peer-reviewedOptimizing processing conditions to achieve a critical quality attribute (CQA) is an in...
Abstract- A tablet press is a mechanical device that compresses powder into tablets of uniform size ...
The aim of this study was to optimize fluid bed granulation and tablets compression processes using ...
We previously determined “Tableting properties” by using a multi-functional single-punch tablet pres...
This study illustrates the application of experimental design and multivariate data analysis in defi...
We developed a new machine learning-based method in order to facilitate the manufacturing processes ...
This paper aims at improving the performance of the tableting process using statistical quality cont...
Optimizing tablets ’ quality with multiple responses using fuzzy goal programming Abbas Al-Refaie1, ...
This case study discusses the use of statistical process control (SPC) for evaluating tablet compres...
Optimizing processing conditions to achieve a critical quality attribute (CQA) is an integral part o...
Context: Tableting is a complex process due to the large number of process parameters that can be va...
This study optimized the performance of plastic extrusion process of drip irrigation pipes using fuz...
To have effective production planning, it is necessary to control the quality of processes. This pap...
In this study, an empirical predictive model was developed based on the quantitative relationships b...
Despite the high quantities of tablets produced daily, many tableting processes are still operated a...
peer-reviewedOptimizing processing conditions to achieve a critical quality attribute (CQA) is an in...
Abstract- A tablet press is a mechanical device that compresses powder into tablets of uniform size ...
The aim of this study was to optimize fluid bed granulation and tablets compression processes using ...
We previously determined “Tableting properties” by using a multi-functional single-punch tablet pres...
This study illustrates the application of experimental design and multivariate data analysis in defi...
We developed a new machine learning-based method in order to facilitate the manufacturing processes ...