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The author of the ppaer titled "Quality Assessment through Analytical Tools and Techniques" discusses several issues ranging from analytical tools that measure the level of quality to procedure that leadership of A-packages can adopt to avoid losses…
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Quality Assessment through Analytical Tools and Techniques
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Quality Assessment through Analytical Tools and Techniques
Introduction
The A-packages company is specialized in the designing and manufacture of plastic containers that are applicable for general household purpose including the kitchen. The overall agenda and objective of A-packages Company is to produce high quality products that are marketable and popular among its customer as are sold in retail and wholesale. A-packages Company has a strong workforce that is passionate in innovating new products causing it to remain a lead in the market. R&D group, the company’s goal movers have developed a product that is durables because the plastic container is able to withstand varied temperatures both low and high. In the recent, the A-packages proposed to endorse and manufacture the new product to address the gap for durable and sustainable product beside glasses that are fragile and plastics that chip quickly. The paper discuses several issues ranging from analytical tools that measure the level of quality to procedure that leadership of A-packages can adopt to avoid losses.
Question A
A1 quality tool
About a decade ago, many business practitioners and academics overlook total quality management in the supply chain supervision in companies however; application of analytical tools is the newest thing in assisting business people to make better decisions that influence a positive change in running ventures. Managers are familiar with analytical techniques as vital in transforming business but the new wave in technology has proved otherwise, because the tools are capable in creation of new opportunities for business innovative (Thorpe et al 2004, 118). In manufacturing companies has adopted the parota analysis to aid in the process of detecting defects in the entire manufacturing process. The A-packages standard material and super new material displayed the following defects, with high rate of air bundles, uneven edges and scratches in the standard material. However, during the fourth week other defect such cracks manifests showing a compromise in the quality of the product. Quality tools are essential in solving such problems related to quality issues in various areas of manufacturing. While in the super new material has similar defects translating from the standard material which could a problem to the process as well the new material. Defects such as cracks, uneven cracks are notable in both material across the weeks as uneven edges and air bubbles being the major defects that seem unsolvable compromising the quality of the product thus non-conforming as there is presence of more than one defects in both materials. It is the reason many manufacturing plants have adapted to different techniques and methods to control their design and production outcome with intention to improve quality. The incorporation by the companies is instrumental for a continuous quality improvement of their products and process as part of systems offered.
Manufacturing companies are in position to use different quantitative and eminence tools to better comprehend the workflow procedures, financial management, innovation implementation that applies in any sector within the manufacturing plant. A decision tree is one of techniques used to help in the decision-making process vital in determining the direction of the business such as facing competitors (Mandal 2009, 8). The decision tree model is a branching graph that displays decisions, possible consequences that might face the company. A-packages top leadership focused on the innovation and profit making instead on investigating further to prevent underlying problems and future obstacles. A thought trough decision is necessary because it identifies strategies essential in attaining a specified goal (Weisberg 2002, 220). The materials faced similar quality issues with same defects hindering the overall quality of the product affecting the company’s reputation of producing good products used in the kitchen and household withstanding numerous pressures. It evident that the super new product failed to meet quality criteria and customer’s need thus rendered poor quality in the market
A2 Advice for the Director of Manufacturing on best choice of action
Just like anyone in top position either in business or leadership, are instrumental in the provision of the right direction without misleading the crowd. The Director of manufacturing has to facilitate the implementation and adoption of a strategic approach in data collection with an aim to evaluate and monitor production processes preventing defects occurrence. In addition, the approach will be essential for both the standard and super new material in return improving the quality of the product because defects are under control. It is the responsibility of the Director of Manufacturer to ensure that the product is of high standard and meets the customer‘s need thus the director has to adopt one of the numerous quality control tools. This will help in indicating the root cause of defects during manufacturer and ways to prevent as well as the trend of the cause as either common cause or special cause variation. Introduction of parota rule analysis and the special cause variation to evaluate defects on product is useful, as it has detailed report about the quality of product, customer complaints and the overall rank in the market
Question B
B1 Control Chart Process
During manufacturing, at no point the quality and characteristics of two products has been exactly same because any process involves several sources and variation. The determination of the overall quality of a finished product is by post-production inspection of the product. According to Jolibert et al (2012, 318) a control chart is important to differentiate special sources of such variation from the ordinary sources. The use of control charts provides a picture of the history of performance as well as ongoing processes that occur over time displaying variations during manufacturing process. According to Oakland (2012, 76) control charts provide additional information aimed at helping manager on how to react, in response to new ideas.
(4+2+2+3+4) = 15
(3+1+2+3+4) = 13
(1+2+2+3+2) = 10
(1+0+4+0+2) = 7
(1+2+1+2+0) = 6
(6+6+4+3+7) = 26
(2+2+3+2+1) =10
(2+0+2+1+3) =8
(1+0+2+1+2) =6 0
(0+1+0+1+0) =2 0
(4+3+2+4+3) = 16
(2+1+0+2+3) = 8
(3+1+1+0+3) = 8
(3+1+1+2+0) = 7
(0+1+1+2+0) = 4
(4+4+4+3+3) = 18 0
(4+3+2+4+3) = 16 0
(3+1+1+2+3) =10
(0+1+0+2+2) = 5
A control chart diagram for both standard and super new material
ANALYTICAL COMBINED CONTROL CHART OF STANDARD MATERIAL
ANALYTICAL COMBINED CONTROL CHART OF SUPER (NEW) MATERIAL
REPORT
From the control chart diagram, the processes involving the analytical projection of the standard material and the super plastic material, it shows that at the beginning of the process, production was above average as indicated by the majority of spots were around the zone C of the upper control limit UCL. The process then progresses to the lower control limit that also falls within zone C, indicating some instability in production of the super new material in the initial stage as defects were noted that were displayed throughout the entire manufacturing process of the new plastic material indicating that the outcome defects were not relatively out of control.
B2-subject to the defect material
A-packages, a company with a good reputation of producing quality product in the past, it is evident that the company subjected both the standard material and super plastic material to defects. The company’s main aim adopting the super new material was to improve their traditional material, as there was slight indication to advance the quality of products in the market. This was because the super new material was adopted to increase the durability and effectiveness of the product.
B3- Advice to Director Manufacturing as per the results
Total quality management is very essential in helping a company to identify, analyze processes, ideas, causes and effective concerns facing manufacturing companies in this global era. The quality techniques provide a platform to examine the effectiveness and efficiency of practices involved in production of a standardized product with fewer defects in the market ( Suganthi, 2004, pg 190). A-packages R&D team should employee a detailed research on the new material and top directors focus on the inclusion of quality tools in future business engagements to avoid speedy decision that are not tangible and only dwells on the promising profit. Several forms of quality tools are available and important in running any type of the business to ensure continuous production of quality products that will enable the package to remain relevant in the market for a long time.
List of References
Charantimah, T. 2003, Total quality management. New Delhi: Pearson Education India. Pg 272.
Jolibert, A, Muhlbacher, H, Flores, L & Dubois, P. 2012, Marketing management: a value-creation process. Washington; Palgrave Macmillan. Pg 488
Thorpe, B & Sumner, P. 2004, Quality management in construction. Leading construction series. Gower Publishing, Ltd., 2004. Pg 216
Mandal, S. 2009, Total quality management - principles and practice, 1E. Canada; Vikas Publishing House Pvt Ltd. Pg 412.
Wrisberg, N & Helias, A. 2002, Analytical tools for environmental design and management in a systems perspective: the combined use of analytical tools. Volume 10 of Eco-Efficiency in Industry and Science. Canada: Springer Science & Business Media. Pg 275.
Suganthi, L & Anand, S. 2004, Total quality management: New York. PHI Learning Pvt. Ltd. Pg 408
Summers, R. 1998, Analyzing operations in business: issues, tools, and techniques. ABC- Clio ebook. Canada: Greenwood Publishing Group, Pg 234.
Oakland, J. 2012, Statistical process control. New Jersey: https://www.google.co.ke/search?tbo=p&tbm=bks&q=inauthor:%22John+S+Oakland%22&source=gbs_metadata_r&cad=6.
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