This study is aimed to investigate the association between anaerobic․aerobic exercise intensity and hand steadiness. Hand steadiness is the decisive contributor to affecting the job performance just as in the rifle shooting and archery in sports and the microscope-related jobs requiring hand steadiness in industries. In anaerobic exercise condition hand steadiness is measured through hand steadiness tester having 9 different diameter holes after each subject exerts 25%, 50%, 75%, and 100% of maximum back strength. In aerobic exercise occasion it is evaluated at each time heart rate reaches 115%, 130%, and 145% of reference heart rate measured in no task condition after they do jumping jack. The results indicate that an increased intensity in both types of exercise reduces hand steadiness, but hand steadiness at 25% of maximum back strength and 115% of reference heart rate is rather greater than at no exercise. Just as the relation between cognitive stress and job performance has upside-down U form, so does the association of physical loading to hand steadiness, which means that a little exercise tends to improve hand steadiness in comparison with no exercise.
We consider a problem of presort and loading of commercial bulk mails in a mailing service. Here, presort is the process by which a mailer prepares mail so that it is sorted to at least the finest extent required by the mailing service provider for the (discounted) price claimed. The problem is formulated as a special type of transportation problem. To solve industrial-sized problems, we develop an efficient heuristic algorithm and perform experimental tests on randomly generated problem instances. Results of the tests show that mailers can save mailing cost much more when they use small-sized mail trays with less frequent mailings. Also, large-sized mailers can obtain much more cost saving than small-sized mailers. In addition, cost saving effect is influenced by delivery area distribution of mails and fluctuation of mailing demand.
This study analyzed the efficiencies of Korean fisheries cooperative’s 97 operation offices in the capital and surrounding area. We used the DEA model for checking the technical and scale efficiencies in the financial business of them. We divided the business into two parts, the productivity (efficiency for increasing deposit and loan) and profitability (efficiency for increasing the profit and reducing the risk from the loan). The results show that the additional profitability increase is very difficult because most of the offices have full technical efficiency for profitability. But additional analysis based on Slack-based Measure (SBM) DEA model shows that Kyung-Gi region can increase the profitability. SBM model analysis also gives us the possibility that customized policy can apply to each offices considering each factors affecting the productivity and profitability.
A cell formation approach based on cluster analysis is developed for the configuration of manufacturing cells. Cell formation,
which is to group machines and parts into machine cells and the associated part families, is implemented to add the flexibility
and efficiency to manufacturing systems. In order to develop an efficient clustering procedure, this paper proposes a cluster
analysis-based approach developed by incorporating and modifying two cluster analysis methods, a hierarchical clustering and
a non-hierarchical clustering method. The objective of the proposed approach is to minimize intercellular movements and maximize
the machine utilization within clusters. The proposed approach is tested on the cell formation problems and is compared with
other well-known methodologies available in the literature. The result shows that the proposed approach is efficient enough to
yield a good quality solution no matter what the difficulty of data sets is, ill or well-structured.
Many retailer store managers are experiencing the situation where some customers balk at purchasing products if the stock is low. In this paper, we extend the single period newsvendor model in an environment of customer balking behavior occurring at double threshold inventory levels assuming the chance of sales during balking is a discrete function of inventory level. Our analysis is based on the assumption that only the mean and the variance of demand are known, without assuming any specific distributional form. We derive the explicit general expression of optimal order quantity with unknown distribution of demand with double threshold inventory levels of customer balking. Then, we illustrate the concepts developed here through simple numerical examples and conclude the future research topics under balking situation.
For evaluating participation in collaboration project, the peer assement method is mostly used and various scoring methods have been proposed. But, the reliability and validity of the peer assessment method are still doubted for all most method. In order to overcome these weaknesss, some guidelines and training methods have been recommended. In this article, however, statistical technique is proposed for measuring individual contributions to collaboration projects considering each assessor’s reliability. The gist of our proposed algorithm is that an assessor’s reliability depends on the evaluation policy, and this reliability is evaluated by an analysis of variance of the scores assigned by the assessor. We also show that the proposed method is very efficient by case study in university class.
Several different depreciation systems may be used for group depreciation. The vintage group procedure treats the same type of property placed in service during the same year as a distinct group for depreciation purposes; therefore an estimate of the probable average service life and net salvage ratio(s) of each individual vintage is necessary. The vintage group procedure calculates an accrual rate for each vintage and the accrual rate for an account for specific calendar year is the weighted average vintage accrual rate for that calendar year. A further refinement would be to divide each vintage into groups such that all of the dollars in a group have the same estimated life-an equal life group (ELG). Then each ELG is depreciated over its estimated life. The effect is to recover each dollar over the estimated number of years it is in service. Each vintage is divided into several equal life groups (ELGs) such that all the property in a specific ELG has the same estimated life. The accrual rate for each ELG is based on the estimated life of that ELG. The vintage accrual rate for a specific year is the weighted average ELG accrual rate for that calendar year. In this paper, we illustrate the calculations of vintage accrual rates for each of the calendar years by the ELG depreciation systems.
Using the known result of the expected busy period for the triadic Med (N, T, D) operating policies applied to a controllable M/G/1 queueing model, its upper and lower bounds are derived to approximate its corresponding actual values. Both bounds are represented in terms of the expected busy periods for the dyadic Min (N, T), Min (N, D) and Min (T, D) or Max (N, T), Max (N, D) and Max (T, D) with the simple N, T and D operating policies without using any other types of triadic operating policies such as Min (N, T, D) and Max (N, T, D) policies. All three input variables N, T and D are equally contributed to construct such bounds for estimation of the expected busy period.
In ubiquitous computing, shared environments adjust themselves so that all users in the environments are satisfied as possible. Inevitably, some of users sacrifice their satisfactions while the shared environments maximize the sum of all users’ satisfactions. In our previous work, we have proposed social welfare functions to avoid a situation which some users in the system face the worst setting of environments. In this work, we consider a more direct approach which is a preference based clustering to handle this issue. In this approach, first, we categorize all users into several subgroups in which users have similar tastes to environmental parameters based on their preference information. Second, we assign the subgroups into different time or space of the shared environments. Finally, each shared environments can be adjusted to maximize satisfactions of each subgroup and consequently the optimal of overall system can be achieved. We demonstrate the effectiveness of our approach with a numerical analysis.
The theory of two-dimensional quality, in particular, the Kano model that is developed by the analogy with the M-H theory, has been applied in various industry fields for more than three decades. Importance-Performance Analysis (IPA) assumes that the degree of physical fulfilment of quality attributes and the satisfaction of that attribute is linear, and therefore, it is applicable to the traditional one-dimensional attribute, not other quality types defined in the Kano’s model such as attractive or must-be attribute. To solve this problem, the current study suggests a new importance-satisfaction analysis using a modified IPA in accordance with the three quality types and a diagonal method introduced by Slack (1999) to determine improvement priority. For this, I investigated 19 smartphone’s quality attributes and conducted a survey of 334 university students for the results of Kano’s model, which adopted from Song and Park (2012)’s study, and the importance/satisfaction of the quality attributes and the results of the priority for improvement of the 19 quality attributes. The results show that the proposed I-S priority model is better than the conventional IPA based on the comparison results of determination coefficient from the regression analysis of the two models.
Since the basic built-in-test, prognostic health management (PHM) has evolved into more sophisticated and complex systems with advanced warning and failure detection devices. Aerospace and military systems, manufacturing equipment, structural monitor- ing, automotive electronic systems and telecommunication systems are examples of fields in which PHM has been fully utilized. Nowadays, the automotive electronic system has become more sophisticated and increasingly dependent on accurate sensors and reliable microprocessors to perform vehicle control functions which help to detect faults and to predict the remaining useful life of automotive parts. As the complication of automotive system increases, the need for intelligent PHM becomes more significant. Given enormous potential to be developed lays ahead, this paper presents findings and discussions on the trends of automotive PHM research with the expectation to offer opportunity for further improving the current technologies and methods to be applied into more advanced applications.
The distribution cost increases constantly because of the growth of yield, globalization of accounts and the generalization of e-commerce. This paper is concerned with scheduling on the allocation of workers to maximize the amount of order process in warehouse logistics system. The problem is to determine the number of operators in each process by the sequential time zone. We considered that the number of operators is restricted to the current level and also the process time is changed by putting some resources into the process. In each stage, we suggest some considerations for the allocation of workers and estimate the maximum amount of order process of the alternatives. We analyzed the alternatives using simulation s/w Arena with real cases.
This paper makes a detailed comparison between two metrics designed for measuring customer’s satisfaction in the retail industry. The first metric, which is called the customer service level, has not been widely used due to the intrinsic requirement on the parameter assumption(s) of the demand distribution. Unlike the customer service level metric the in stock ratio metric does not require any requirements on the demand distribution. And the in stock ratio metric is also very easy to understand the meaning. To develop the detailed planning activities for business with the in stock ratio metric on hand one should collect some information as following : 1) POS (Point of sales) data, 2) Inventory Data 3) Inventory Trend.