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The primary goal of employing the improvement model referred to as Six Sigma is to limit variations in organizational outcomes whether as a transaction, product, or process. Through the application of statistical methods, any operating entity can use Six Sigma to enhance system performance (Stevenson, 2018). It was first developed as a quality control measurement tool towards improving the manufacturing and inspection processes at Motorola given that conventional means failed to detect and rectify defects (Stevenson, 2018). Statisticians employ the Greek alphabet, Sigma (σ) to represent standard deviation. Six Sigma translates to six standard deviations which entail working towards 3.4 defects for every one million outcomes (Stevenson, 2018). By studying the application of Six Sigma in an Egyptian plastic molding company, it is evident that quality of the end product is considerably enhanced thus allowing for cost effective operational processes, satisfied customers, and cleaner environment.
An Inefficient Plastic Injection Molding Process
The development of modern day plastics continues to be kept afloat by strong consumer demand. However, as witnessed in the Egyptian plant, plastic production techniques are often faced with challenges in achieving consistently good quality products (Maged et al., 2019). The company identifies the plastic injection molding process as a critical production phase. It involves the conversion of hot melt into pre-designed plastic products for specific purposes. Raw thermoplastic material is first melted before injection at immense pressure into a pre-designed cast. The Egyptian firm sells products with plastic parts like irons, fans, choppers, and blowers (Maged et al., 2019). The largest manufacturing process within the company involves the production of a diverse array of plastic components.
Unfortunately, it is common to encounter numerous plastic injection molding processes producing unfavorable outcomes. These include the production of huge quantities of defective plastic parts (Maged et al., 2019). These non conforming parts cannot be used in the rest of the production process and are thus considered as plastic scrap. The Egyptian firm terms such outcomes as being very costly in terms of time and organization resources, especially when it comes to reclaiming them for reuse (Maged et al., 2019). The firm is also keen on conforming to environmental regulations put in place by the Egyptian government. This involves ensuring that waste management processes attain high levels of efficiency when disposing defective materials. The best way to cut back on operational losses and to keep in line with government regulations is for the firm to lower the rate of production relative to plastic scrap (Maged et al., 2019). It determined that such goals can only be achieved through a continuous improvement process protocol using Six Sigma to keep the scrap rate at a minimum while also ensuring it avoids environmental degradation.
Application of Six Sigma for Improvement of the Plastic Injection Molding Process
Six Sigma works to indentify and subsequently prioritize problems encountered in a particular organizational processes. Its ultimate goal is to gain comprehension of an entity’s operational processes prior to controlling variations in outcomes (Stevenson, 2018). The variations result from issues relating with measurement, methods, machines, materials, manpower and Mother Nature (Uluskan, 2016). One can further categorize problems to be solved as those associated with limiting the unreliability of operational processes, eliminating wastages, identifying and cutting back on defective outcomes, minimizing process costs, and enhancing customer satisfaction (Uluskan, 2016). This basically means that the objective of deploying Six Sigma is to enhance productivity, appraise profitability, and improve customer satisfaction (Stevenson, 2018). Six Sigma utilizes two fundamental methodologies. The first method is applied for the improvement of existing processes by working to define, measure, analyze, improve, and control (DMAIC) outcomes (Uluskan, 2016). The second method is employed in the designing of fresh processes by working to define, measure, analyze, design, and verify them (DMADV).
Relative to the defects occurring in the plastic injection molding process, reasons for undesirable outcomes are attributable to labor skills, machine performance, processing conditions, part designs, materials used, and mold design (Maged et al., 2019). Upon careful scrutiny, it is observable that part design was fixed while mold design issues were kept at a minimum using computer assisted design development, simulation, and prototyping. The issue with materials used with regard to quality of both the inputs and outputs was critically examined towards identifying optimal parameters. Process stability for production operations was found to be undermined by noise factors (Maged et al., 2019). Using the DMAIC model, it was envisaged that existing process would realize desired improvements.
In this phase, a number of tasks were conducted in accordance with the adopted quality improvement methodology. This involved establishing a feasible scope for the project, goal setting, and establishing project conditions (Stevenson, 2018). Since the firm cited resource deficiencies, the project’s timeframe was limited to six months (Maged et al., 2019). The project’s goal was stipulated as ensuring robustness and stability in the production process by limiting the number of defective components generated from the plastic injection molding process. To define the issue of a high rejection rate, the cost associated with poor quality were termed as those that would be eliminated in processes, systems, and products are perfected. The cost of poor quality parts was established for each model so that the one with the highest cost was prioritized as the study element.
The measurement phase sought to pinpoint particularly essential product characteristics of the prioritized model part. The measurement system applied involves gauges, measure, software, instruments, methods, operations, and personnel. It was evident that ensuring necessary measurements were attained is critical to accurately examining process performance (Uluskan, 2016). Over a five month period, the rejected numbers of the prioritized model parts were tabulated. They were first inspected visually prior to caliper tools being applied to measure a distinct part of the produced plastic component model. After the five month duration, a considerably low sigma level was achieved relative to the conventional process output since the operations adopted a more prudent confidence level (Maged et al., 2019). The next phase of the quality improvement process was to identify factors resulting in defects in the measured part.
This step starts by determining which particular defect of the prioritized plastic model that the project team is to begin with. Over the course of five months, it was established that defects associated with shrinkage resulted in the largest number of rejects (Maged et al., 2019). This was caused by a considerable deviation in diameter of the part under investigation. The project team implementing the Six Sigma model engaged in a number of sessions to pinpoint causes and important variables that resulted in the occurrence of that particular type of defect (Uluskan, 2016). Using a cause and effect chart, areas where no impact of defect was established led to the probable variable being eliminated. At the close of this phase of the Six Sigma model, the project team established the need to consider actions deemed as critical to achieving the set goals.
In many cases where the Six Sigma model is employed to enhance existing processes, the Improve phase is considered as the most challenging one to implement. For instance, considering that shrinkage is the major cause of defects in the prioritized plastic model, correctly predicting when this takes place is often a significant improvement strategy (Maged et al., 2019). The aim is to pinpoint on what action to implement if a defect does occur. This is an effective means of identifying a solution and avoiding future prevalence of that specific undesirable outcome. This implies using an optimal control chart to inform which countermeasures to take. This essentially acts as a means of analyzing the root cause of the defect and using countermeasures to remove it and gain control of the process as intended (Uluskan, 2016). The aim is to ensure that this particular phase is repeated towards progressively reducing the number of rejections in the production process.
This is the final phase in the deployment of DMAIC Six Sigma towards achieving desirable quality improvement outcomes. The project’s goal was stipulated as ensuring robustness and stability in the production process by limiting the number of defective components generated from the plastic injection molding process (Maged et al., 2019). The main aim of this stage is to ensure sustained production at optimum levels. However, this poses a considerable challenge for this particular improvement approach as it requires constant monitoring, standardization, and control of optimized operational processes (Uluskan, 2016). Through the application of control charts, the personnel concerned can engage in preventive action to curtail the number of undesirable parts from exceeding control limits. Through the monitoring process, it is possible to notice out-of-control pointers and thus make corrective action to stem production losses.
It is apparent that the Six Sigma approach to achieving continuous quality improvement is resource intensive. For instance, it demands that the project be undertaken with well trained team members devoting a large amount of their time to the actualization of the entire process. It is for this reason that it employs quantitative as well as qualitative tools that enhance achievement of project goals. As indicated, attaining project objectives begins by identifying which problem needs to be defined, measured, analyzed, improved, and controlled before it is generalized across the entire process. The fact that it works to eliminate major defects is indicative that it also appraises personnel development. This is relative to how the process works and how other defects can be collaboratively worked out to enhance quality, efficiency, and effectiveness of all organizational processes.
Maged, A., Haridy, S., Kaytbay, S., & Bhuiyan, N. (2019). Continuous improvement of injection moulding using Six Sigma: case study. International Journal of Industrial and Systems Engineering, 32(2), 243-266.
Stevenson, W. J. (2018). Operations management, (Thirteenth Edition). New York, NY: McGraw-Hill/Irwin.
Uluskan, M. (2016). A comprehensive insight into the Six Sigma DMAIC toolbox. International Journal of Lean Six Sigma, 7(4), 406-429.