Process Variability Analysis of License Vehicle Number Plate Production in Nigeria (original) (raw)
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Process variability analysis in make-to-order production systems
Cogent Engineering, 2016
Vehicle license number plate production in Nigeria faces high variability in terms of process times and inter-arrival times, resulting in poor production schedule reliability. This study aims to clarify the level of such variation and to provide process improvement strategies within plate production. The specific objectives herein include identifying assignable variables, estimating variability indices and minimizing variation by developing solutions to improve system performance. This study explores the variability pooling method in assessing potential cost-effective process improvements and a case study is conducted on four Nigerian vehicle license number plate production plants in order to demonstrate the applicability of the proposed technique. Structured questionnaires were circulated to plant workers and data collected from plant production records from 2012 to 2015 in seven production lines were analyzed. A preliminary study on the production lines revealed the coefficient of variation (CV) for the Awka, Gwagwalada, Lagos and Lagos State Plants, showing measured variability levels of 0.62, 0.67, 0.60 and 0.78, respectively. Comparatively, the results obtained after the variability pooling showed a significant improvement in performance characteristics, such as low CV levels, enabling a 68% increase in net annual income for each plant, as well as enhanced machine utilization.
Balancing a multistage vehicle number plate production line using effective cycle time model
2020
Shortest product cycle time is a key criterion for job sequencing and measuring competitiveness among entrepreneurial-based firms. Now, the long waiting time of job orders constitutes a deterministic production line problem in vehicle number plate production plants in Nigeria. Case studies were conducted on those plants, confidentially identified in this paper as A, B, C, and D. Delays caused by non-value-adding work processes are major culprits among other contributors to the long queues at these plants. The value stream mapping technique was applied to identify non-value adding activities before the production line was balanced using an effective cycle time model. The index cases to a balanced line, as shown in the results, are increases in process rate by 41 %, 59 %, 42 %, and 71 % for A, B, C, and D, respectively, and overall line efficiency. Next, the system capacities correspondingly increased with the elimination of wastages. These increments imply that bottleneck activitie...
An Examination of Variability and Its Basic Properties for a Factory
IEEE Transactions on Semiconductor Manufacturing, 2005
Variability is a key performance index of a factory. In order to characterize variability of a factory, definitions of bottleneck, utilization, and variability of a single machine are reexamined and clarified. The clarification leads to the introduction of a detail expression for the relationship between cycle time and work-in-progress. In order to quantify variability for factories, the author uses a single machine system to gauge the behaviors, and subsequently derives an explicit expression for the variability, of a simple factory, making use of analogy and the clarified definitions. The obtained results can be applied to many subjects in the field of manufacturing management, such as factory performance analysis, capacity planning, and cycle time reduction. With the derived results, properties of variability for a simple factory in the aspects of utilization versus throughput bottlenecks and nonthroughput bottlenecks, gap effects, and bounds on variability, are examined in detail to shed light on the insights of the stochastic behaviors of a complex factory.
Variance Analysis in Manufacturing Companies
Proceedings of the 1st International Scientific Conference - FINIZ 2015, 2015
In dynamic and constantly changing contemporary business conditions, it is of key importance to dispose of adequate and relevant information on movements in the manufacturing process and to make adequate business decisions. Traditional accounting is not able to respond to all challenges, and thus it is necessary to enable better understanding of the manufaturing processes and the effects of various factors on the final outcomes and product costs. Several different models of cost accounting have been proposed with certain advantages and flaws, depending on the complexity of production and management requirements. Variance analysis is a tool that financial controllers and corporate financial managers use to interpret variations in operating results compared to the result envisaged by the budget or budget revision throughout the year. The aim of this paper is to analyse the effects of variance analysis in the manufacturing company as a result of its good managerial accounting. The subject of this paper is one company, and its course from the budget as the basis for implementation of variance analysis, to realization and explanation of discrepancies between these two scenarios.
Improving Efficiency and Reliability of Manufacturing Systems by Variability Placement
Variation is one the primary causes for degrading line efficiency and building excess inventory in a manufacturing process. This paper focuses on modeling the effects of different degrees of variation (high, medium and low) at different location in a manufacturing process. A simulation study applies design of experiments to determine the influence of different types of variations on the performance measures. The process performance measures considered are throughput, work in process, value added time, wait time, and total output of the process. This study identifies the location and level of improvement in a process to increase the overall gain in performance measures and reliability of the manufacturing process.
Analysis of the Output Variance in Production Lines: Methodology and Applications
Most of the research efforts have been spent on the development of efficient methodologies to estimate the first moment performance measures of production systems, such as the expected production rate, buffer levels and lead times. However, the variability of the production output may drastically impact on the capability of managing the system operations, causing the observed system performance to be highly different from what expected. This paper presents an efficient method to estimate the variance of the number of parts produced, in a given time period, by production lines composed of unreliable machines. Design of Experiments is adopted to study the accuracy and the speed of the proposed algorithm with respect to simulation, which is an alternative approach to study the variance of the output of unreliable multi-stage lines. Furthermore, the effectiveness of the proposed approach is proved through the analysis of two real cases in the liquid bottling sector.
This paper presents a case study in the development and application of a mathematical model to optimize the production capacity of Number plate plant in Nigeria which is into the production of different grades of Number plates. The motivation of this study was borne out of the need to clearly explain the role of time gap as an impetus for nefarious activities in the Vehicle Number plate production and how it can be tackled using time-based mathematical model. The study reveals that 10000 units of Number plate would be produced in 83.33hrs and there is need to increase the efficiency of the production system to meet up with the drive of sanitizing the motor vehicle administration.
Controlling Production Variances in Business Processes
Springer, Cham, 2018
Products can consist of many sub-assemblies and small disturbances in the process can lead to larger negative effects downstream. Such variances in production are a challenge from a quality control and operational risk management perspective but also it distorts the assurance processes from an auditing perspective. To control production effectively waste needs to be taken into account in normative models, but this is complicated by cumulative effects. We developed an analytical normative model based on the bill of material, that derives the rejection rates from the underlying processes without direct measurement. The model enables improved analysis and prediction. If the rejection rate is not taken into account the function of the bill of material as a reference model deteriorates and therefore output measures become more opaque and harder to verify. As a consequence it is extremely difficult or even impossible to assess efficiency and effectiveness of operations. Secondly it is impossible to judge whether net salable assets represent the correct amount and finally it is impossible to assert whether the operations do comply to company standards and applicable laws.
Understanding of Production Cost Variances in Hectic Business Environment
2010
Production cost management is one of the most crucial factor of a successful company, in this paper I show a methodology how can we track variable costs, what kind of analytical tool can we have if we want to understand the variances of the production cost versus expectations. Nowadays during economic crisis the real world can be far from the expectation of the management, so it is important to understand if the drivers of the variances caused by internal or external factors. In this methodology the reasons of the variances can be caused by some external circumstances, like inflation and due to some operational issue, like variable cost productivity. This methodology can help to understand key drivers of cost differences, and can help to measure the efficiency of manufacturing function within the company.