Design of the optimal feeding policy in an assembly system

This paper describes an innovative and integrated approach to component management optimization within a production/assembly system. In a mixed-models assembly process the handling of parts and components for each work station represents a substantial variable that can greatly affect job duration and efficiency. This paper is strictly related to Assembly to Order/Manufacturing to Order (ATO and MTO) systems, where lead time has to be very short and flexibility is at its maximum level. In Assembly to Order (ATO) or Make to Order (MTO) systems, the production is increasingly getting more customized in response to the demand, thanks to the progresses reached in both manufacturing and information technologies. It is becoming increasingly possible to assemble or make products specifically in response to the requests of either end customers or retailers. As a consequence of such customization, the design of the whole system must take into direct account several elements: parts warehouses location, feeding policies and feeding systems. In some cases the collection of parts and components required picking activities, in other the movement of entire units load.In several instances experts have analyzed the problems about material centralization/decentralization, storage policies and assembly feeding problem in different and independent ways, while the problem needs an integrated approach. While many researches regarding components allocation problems in ATO and MTO systems, did not consider feeding policies, material picking, packing activities and vehicles optimization, this paper cover focuses on filling such gap using an integrated framework that considers both aspects of the problem: the centralization/decentralization of components in order to minimize the total storage costs and the right feeding policies.Feeding problems in assembly lines are some of the most important aspects to consider during the analysis and design of an assembly system, to allow the maximization of efficiency and flexibility. To reach such goals, a multi-factorial analysis has been carried out during this experiment and will validate the introduced framework. An industrial application of the introduced framework is illustrated to explain its real significant production implication.     

The influence of an optimal control system on salesperson performance and championing

In this study, the effect of a deviation from an optimally blended control system on salesperson performance and championing is investigated. Blended control systems represent combinations of many different forms of control, affording sales managers the opportunity to better match a control system with the overall context in which their firm operates, addressing such things as current salesperson, firm, and environmental variables. The extent to which the blended system represents an appropriate match with the overall context, however, is of primary concern. As demonstrated here, deviations from optimal control negatively affect both individual salesperson performance, as well as salesperson championing. In combination, these findings emphasize the importance of understanding a broader picture of salesperson control than is allowed through simple direct effect analysis.     

Analysis of a general Markovian two-stage continuous-flow production system with a finite buffer

Fluid flow models are used in the performance evaluation of production, computer, and telecommunication systems. In order to develop a methodology to analyze general Markovian continuous material flow production systems with two processing stages with an intermediate finite buffer, a general single-buffer fluid flow system is modelled as a continuous time, continuous-discrete state space stochastic process and the steady-state distribution is determined. Various performance measures such as the production rate and the expected buffer level are determined from the steady-state distributions. The flexibility of this methodology allows analysis of a wide range of models by specifying only the transition rates and the flow rates associated with the discrete states of each stage. Therefore, the method is proposed as a tool for performance evaluation of general Markovian continuous-flow systems with a finite buffer. The solution methodology is illustrated by analyzing a production system where each machine has multiple up and down states associated with their quality characteristics.     

Approximation approach for the performance analysis of production lines under a kanban discipline

In a JIT production environment, pull-type control systems are usually implemented to reduce the lead time and to synchronize the production rate with the demand rate. The design of an effective production control system requires easy and reliable approaches for evaluating the effect of the major system parameters on its performance.In this paper we model the kanban control system of a manufacturing line as a Markov process. In addition, we develop an approximation approach to the model that permits reliable evaluation of manufacturing system performance in terms of throughput time and work-in-process. The validation of the approach is implemented by comparing the exact results (based on discrete event simulation) and the approximated results.A good approximation is observed for a large range of conditions.     

Feel free to feel comfortable—An empirical analysis of ergonomics in the German automotive industry

The purpose of this paper is to examine ways to improve ergonomics on the manufacturing shop floor. In particular, the impact of certain ergonomic practices on companies' economic and social objectives is investigated empirically. In order to do so, a survey has been conducted among manufacturing managers of 55 companies in the German automotive industry. The managers have been asked about their estimations on harmful tasks within the production process and on the effectiveness of various practices in the context of ergonomics and health. Worker-oriented and work-oriented practices of ergonomics are operationalized using factor analysis. By means of a cluster analysis, companies with a high degree of implementation of ergonomic practices are identified. The analysis shows that plants with a higher implementation degree of ergonomic practices show a better performance in terms of economic and social objectives. Furthermore, the results reveal that work-oriented practices lead to better performance with respect to the investigated economic and social objectives, whereas worker-oriented practices play a supporting role only. Finally recommendations for manufacturing companies with regard to the field of ergonomics are derived from the empirical results.     

基于灰色系统关联分析的施工企业安全投资研究

分析了我国建筑施工安全生产的现状和诱因,指出安全投资不合理是导致建筑安全事故发生的主要因素之一。在明确安全投资内涵及构成的基础上,针对安全系统的不完全信息性,运用灰色系统关联分析理论,建立了安全投资灰色关联模型,对安全系统的关联度进行综合评价,找出影响安全投资结构的最主要因素,并优先将其作为安全投资方向,为施工企业进行安全投资决策提供理论依据。     

An economic analysis of the optimal information security investment in the case of a risk-averse firm

This paper presents an analysis of information security investment from the perspective of a risk-averse decision maker following common economic principles. Using the expected utility theory, we find that for a risk-averse decision maker, the maximum security investment increases with, but never exceeds, the potential loss from a security breach, and there exists a minimum potential loss below which the optimal investment is zero. Our model also shows that the investment in information security does not necessarily increase with increasing level of risk aversion of the decision maker. Relationships between vulnerability and investment effectiveness and two broad classes of security breach probability functions are examined, leading to interesting insights that can be used as guidelines for managers to determine the optimal level of security investment for certain types of security threats faced by risk-averse firms. Future research directions are discussed based on the limitations and possible extensions of this study.     

A case study of condition based maintenance modelling based upon the oil analysis data of marine diesel engines using stochastic filtering

This paper presents a case study of condition based maintenance modelling based on measured metal concentrations observed in oil samples of a fleet of marine diesel engines. The decision model for optimising the replacement time of the diesel engines conditional on observed measurements is derived and applied to the case discussed. We described the datasets, which were cleaned and re-organised according to the need of the research. The residual time distribution required in the decision model was formulated using a technique called stochastic filtering. Procedures for model parameter estimation are constructed and discussed in detail. The residual life model presented has been fitted to the case data, and the modelling outputs are discussed.     

Design of a novel adaptive inventory control system based on the online identification of lead time

In this paper, an adaptation method for the online identification of lead time is incorporated in production–inventory control systems. Based on the lead time estimate, the tuning parameters are updated in real time to improve the efficiency of the system. Combination of the adaptive scheme with a proportional control law is able to eliminate the inventory drift that appears when the actual lead time is not known in advance or when it varies with time. A detailed analysis is provided for the proposed production–inventory system, including a stability analysis and the quantification of its bullwhip effect. Several examples and comparison with state-of-the-art alternative approaches illustrate the efficiency of the system.     

A bicriteria approach to maximize the weighted number of just-in-time jobs and to minimize the total resource consumption cost in a two-machine flow-shop scheduling system

We analyze a two-machine flow-shop scheduling problem in which the job processing times are controllable by the allocation of resources to the job operations and the resources can be used in discrete quantities. We provide a bicriteria analysis of the problem where the first criterion is to maximize the weighted number of just-in-time jobs and the second criterion is to minimize the total resource consumption cost. We prove that although the problem is known to be NP-hard even for constant processing times, a pseudo-polynomial time algorithm for its solution exists. In addition, we show how the pseudo-polynomial time algorithm can be converted into a two-dimensional fully polynomial approximation scheme for finding an approximate Pareto solution.     

Sourcing strategies of U.S. service companies: a modified transaction–cost analysis

Global procurement of services has been receiving an increasing amount of managerial attention in recent years. Service firms seem to have begun sourcing part of their service activities from abroad in much the same way as manufacturing firms have sourced components and finished goods in the past 30 years. However, little is known about the nature of service sourcing strategy. In this study, we employ a modified transaction–cost analysis to examine empirically the locational (domestic vs. global sourcing) and the ownership (internal vs. external sourcing) aspects of service sourcing strategy. In addition, performance implications on both the locational and ownership aspects of service sourcing are investigated. The results show that, similar to components and finished goods procurement, supplementary services are sourced globally, either internally or externally. Furthermore, the relationship between asset specificity and internal sourcing of supplementary services is moderated by the level of inseparability and transaction frequency. Finally, internal sourcing and foreign sourcing of supplementary services are negatively related to a service’s market performance. Copyright © 1999 John Wiley & Sons, Ltd.     

Do it separately or simultaneously—An empirical analysis of a conjoint implementation of TQM and TPM on plant performance

Over the last decades, Total Quality Management (TQM) and Total Productive Maintenance (TPM) have become key concepts for improving production. The majority of modern manufacturing companies has implemented at least one of these improvement programs or even both of them. The common ground of TQM and TPM is the focus on human resources. In this paper, the impact of TQM and TPM on plant performance and especially the supporting role of employee involvement practices is investigated empirically using multiple regression analysis and structural equation modeling. The data used for conducting the analyses is taken from the international research project High Performance Manufacturing that contains the data of 238 plants. The results indicate that TQM and TPM, supported by HR practices, have a significant potential to improve plant performance. However, a simultaneous implementation of both concepts does not necessarily lead to superior performance. As potential reason for this, human resources are regarded as limiting factor both improvement programs draw on. Accordingly, this scarce resource is identified as crucial element with respect to performance when implementing TQM and TPM simultaneously.