Biman Das, Alberto Garcia‐Diaz and Clarence L. Hough
For machine‐paced operations a two‐factor monetary incentive planis developed by employing production quantity output and productionwaste as criteria for incentive earnings. The…
Abstract
For machine‐paced operations a two‐factor monetary incentive plan is developed by employing production quantity output and production waste as criteria for incentive earnings. The plan takes into account machine time allowance and increased operator work pace for manual work for establishing standards in a machine‐paced operation. The two incentive earning factors are given proper weights in terms of their relative economic importance. The weights are determined by comparing possible labour and material costs savings when the operators perform at incentive pace level. To demonstrate the working of the proposed monetary incentive plan an illustrative example is presented.
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Biman Das and Alberto Garcia‐Diaz
The lost time arising from travelling and waiting of the production operators and manufacturing inspectors at the tool and gauge crib counters can be considerable in a large…
Abstract
The lost time arising from travelling and waiting of the production operators and manufacturing inspectors at the tool and gauge crib counters can be considerable in a large manufacturing plant. This travelling and waiting time can be eliminated or minimized by consolidating the tool and gauge cribs near the master crib, extending the totebox system and providing a dispatching system. In the proposed system the tools and gauges will be delivered at the workstation by the dispatchers. The new system would improve the utilization of the tool and gauge crib attendant’s time and reduce the tool and gauge inventory. The case problem revealed that a net annual labor cost saving of about $320,600 and a saving of $242,100 from the reduction of tool and gauge inventory could be achieved. The additional floor space requirement would be about 1,700sq. ft and the implementation cost would be about $144,500.
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Biman Das, Alberto Garcia‐Diaz, Corinne A. MacDonald and Kalyan K. Ghoshal
The purpose of this paper is to develop a computer simulation model to evaluate increasing versus decreasing mean operation times assembly line arrangement for normal and…
Abstract
Purpose
The purpose of this paper is to develop a computer simulation model to evaluate increasing versus decreasing mean operation times assembly line arrangement for normal and exponential distributions and the variances equal to 1 and 16.
Design/methodology/approach
The model was developed on the basis of a realistic case problem and applied to a six‐station assembly line. The evaluation criteria were: the minimization of the total elapsed time; the maximization of the average percentage of working time; and the minimization of the average time in the system.
Findings
The increasing mean operation times line arrangement is superior to the decreasing mean operation times line arrangement for the normal and exponential distributions and the variances equal to 1 and 16, in terms of the total elapsed time and the average percentage of the working time evaluation criteria. The decreasing mean operation times lines is marginally superior to the increasing operation times line for the normal distribution for the variances equal to 1 and 16, in terms of the average time in the system evaluation criterion. The above inference can be made for the exponential distribution for the variance 16, but no definitive conclusion can be made for the variance 1. Overall, the increasing mean operation times line arrangement has proven to be superior to the decreasing operation times line arrangement for both the stated distributions and variances, in terms of the important evaluation criteria.
Originality/value
The paper contributes to the computer simulation approach to solving assembly line problems that deal with the impact of normally and exponentially distributed operation times, with variances equal to 1 and 16, on the increasing and decreasing mean operation times assembly line arrangements.
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Biman Das, Jesus M. Sanchez‐Rivas, Alberto Garcia‐Diaz and Corinne A. MacDonald
The purpose of this paper is to develop a computer simulation model to evaluate the bowl phenomenon and the allocation at the end of the line of stations with either greater mean…
Abstract
Purpose
The purpose of this paper is to develop a computer simulation model to evaluate the bowl phenomenon and the allocation at the end of the line of stations with either greater mean operation times or higher variability of operation times.
Design/methodology/approach
The model was developed on the basis of a realistic case problem and applied to a six‐station assembly line. The evaluation criteria were the: minimization of the total elapsed time; maximization of the average percentage of working time; and minimization of the average time in the system.
Findings
The performance of an assembly line with independently normally distributed operation times could be improved by applying the bowl phenomenon. The allocation of large operation mean times to stations located near the end of the line did not produce improved results. Instead a more balanced allocation proved to be more significantly effective. On the other hand, the assignment of larger variability of operation times to the stations near the end of the line improved the performance of the assembly line.
Originality/value
The investigation contributed to the computer simulation approach to solving assembly line problems that dealt with the impact of normally distributed operation times on the bowl phenomenon and assembly lines with increasing mean operation times and higher variability of operation times at the end of the line of stations.
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Pedro Carlos Oprime, Fabiane Leticia Lizarelli, Marcio Lopes Pimenta and Jorge Alberto Achcar
The traditional Shewhart control chart, the X-bar and R/S chart, cannot give support to decide when it is not economically feasible to stop the process in order to remove special…
Abstract
Purpose
The traditional Shewhart control chart, the X-bar and R/S chart, cannot give support to decide when it is not economically feasible to stop the process in order to remove special causes. Therefore, the purpose of this paper is to propose a new control chart design – a modified acceptance control chart, which provides a supportive method for decision making in economic terms, especially when the process has high capability indices.
Design/methodology/approach
The authors made a modeling expectation average run length (ARL), which incorporates the probability density function of the sampling distribution of Cpk, to compare and analyze the efficiency of the proposed design.
Findings
This study suggested a new procedure to calculate the control limits (CL) of the X-bar chart, which allows economic decisions about the process to be made. By introducing a permissible average variation and defining three regions for statistical CL in the traditional X-bar control chart, a new design is proposed.
Originality/value
A framework is presented to help practitioners in the use of the proposed control chart. Two new parameters (Cp and Cpk) in addition to m and n were introduced in the expected ARL equation. The Cpk is a random variable and its probability function is known. Therefore, by using a preliminary sample of a process under control, the authors can test whether the process is capable or not.
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Adilson Carlos Yoshikuni, Rajeev Dwivedi, Claudio Parisi, Jose Carlos Tiomatsu Oyadomari and Ronaldo Gomes Dultra-de-Lima
Enterprise Risk Management (ERM) is a strategy and approach that enables organizations to manage risk strategically from a systems standpoint. The ERM assists businesses in…
Abstract
Purpose
Enterprise Risk Management (ERM) is a strategy and approach that enables organizations to manage risk strategically from a systems standpoint. The ERM assists businesses in structuring their systems to generate strategic flexibility (SF), which leads to increased firm performance (FP) through strategic enterprise management (IS-SEM) and strategic momentum (SM).
Design/methodology/approach
The study is based on data gathered in Brazil and India. The complex link was discovered using partial least square structural equation modeling (PLS-SEM) using 330 Brazilian and Indian sample sizes.
Findings
The findings show that ERM influences IS-SEM and SM, which improves SF and FP. Furthermore, the study claims that IS-SEM can help improve strategic momentum and flexibility in the face of environmental uncertainty (ENU). Thus, it indicated that specific combinations of ENU connected with ERM and IS-SEM lead to obtaining high and extremely high levels fuzzy set qualitative comparative analysis (fsQCA) post hoc analysis of strategic momentum and flexibility.
Practical implications
The findings help executives understand how ERM and accounting information systems (AIS) can help achieve SM and SF, hence promoting FP in situation specific ENU setups in developing economies. The findings enhance executives' comprehension of how ERM and IS-SEM can significantly contribute to achieving SM and SF, thereby driving FP in the situation-specific ENU configurations in developing economies.
Originality/value
Research indicated that specific combinations of (ENU) connected with ERM and IS-SEM lead to obtaining high and extremely high levels fuzzy set qualitative comparative analysis (fsQCA) post hoc analysis of strategic momentum and flexibility.