Analysis of Production Line Quality Using Time Study.

International Journal of Research and Innovation in Applied Science (IJRIAS) | Volume VII, Issue I, January 2022 | ISSN 2454–6194

Analysis of Production Line Quality Using Time Study.

Joy E. Abraham-Igwemoh, O.M.O. Etebu
Department of Mechanical Engineering, University of Port Harcourt. Nigeria.

Abstract
Every industry must devise a technique for evaluating the process output with measurable standard and take remedial action if therezvfr observed time each task was performed relative to the standard time for efficiency computation. The results from the efficiency chart as depicted by the bar chart showed that task F, G, H and G (which required minimum motion) had the highest efficiencies in decreasing order compared to the other tasks. The location model was used to analyze the assembly line to determine suitable possible locations for both facility; storage site and workshop floor that will enhance staff efficiency and improve productivity. The effect of staff age and number of work experience relative to working hour was also evaluated and the result as shown by MS-Excel line plot is that, experience increases performance for technical tasks and is also a function of age while for task requiring human labour (in terms of effort) the younger the staff the higher the level of performance.
Keywords: Time Study, Service Quality, Statistical Process Control, Flow Chart.

I. INTRODUCTION
Service quality is a broad term that is viewed from various perspective encompassing consistency, promptness in resolving customers complaints as well as delivery time etc. Service quality has five major definition approach-product based approach which focuses on the measurable attributes of the service; process-based approach which means compliance to set standards; opposite-demand that is, customer’s satisfaction; Value-approach which is the ratio of provided benefits to acquired cost and finally the philosophical definition that refers to the perfection of service delivery [2]. Owing to the recent competition in all business aspects, service delivery time has become an important factor to consider for continuous business patronage of any firm because time is one of the most important tools in determining a company’s performance [1]. Time can be defined as a component used in measuring systems to arrange and compare events duration and also measure the motion of work element [3]. This parameter can be measured using time study-the time required to perform a specific task at a defined level of performance. Time study is a useful tool for employee’s assessment during appraisal and for computing machine and man-hour for proper job allocation and for conducting quality control and Quality assurance (QC/QA). One of the seven wastes in any industry as identified by lean manufacturing which is ‘waiting’ can be handled by applying this principle. Several researchers have employed time study in solving the problem of productivity in both service and manufacturing industries. [1] in his research to determine the standard time for a man power process was able to maximize production and optimize cost through the application of pro-model to simulate production time, layout and the number of processes. [5] was able to insert five minutes break every production hour maintaining productivity without changing demand or increasing operator’s workload by applying time and motion study techniques to a manufacturing industry. [6] in their work used time and motion study with assembly line balancing to improve the productivity of a firm. The efficiency of a firm in terms of productivity was increased by 53% through the application of time and motion study techniques in the work of [7]. In this research, the productivity of a petroleum servicing company was enhanced by using time study to evaluate and identify the non-value adding operations and bottleneck in the processes resulting in delay in
service delivery. The location model was also applied to restructure the assembly line for increased productivity at minimal cost.

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