SETTING SAFETY LEADTIMES FOR PURCHASED COMPONENTS IN ASSEMBLY SYSTEMS

There are significant amount of literature on the capacitated lot sizing problem(CLSP) with different levels and approaches. In this article, immune complement algorithm (ICA) was discussed in scheduling optimization of CLSP under the condition of single level, single machine. The affinity function was the total cost which including order, inventory carrying and labor costs. Complement individual was represented by binary to determine order sequence and lot sizing. Experimentation performed with 5 production 6 period indicated that ICA had the characteristics of high speed of convergence, less generations besides approaching best solution, and it could be used in CLSP on medium scale.

Multiple-method analysis of logistics costs

I: General Issues.- Modeling Knowledge: Model-based Decision Support and Soft Computations.- Benefits of Decision Support Using Soft Computing.- Evolving Connectionist-based Decision Support Systems.- An Agent-based Soft Computing Society with Application Applications in Financial Investment Planning.- A Rough Sets/Neoral Networks Approach to Knowledge Discovery for the Development of Decision Support Systems.- II: Applications and Implementations.- Decision Support Systems in Healthcare: Emerging Trends and Success Factors.- A View of Public and Private Sectors for Taiwan's BOT Project Financing Using Fuzzy Multi-Criteria Methods.- Relational Structures for the Analysis of Decision Information in an Electronic Market.- A Fuzzy Evaluation Model: A Case for Intermodal Terminals in Europe.- Application of Kemeny's Median for Group Decision Support.- An Internet-based Group Decision and Consensus Reaching Support System.- Limpio: A DSS for the Urban Waste Collection Problem.- A Decision Support System for Air Quality Control Based on Soft Computing Methods.- Multicriteria Genetic Tuning for the Optimization and Control of HVAC Systems.- Intelligent Information Systems for Crime Analysis.- Application of Fuzzy Decision Trees to Reservoir Recognition.- Introducing SACRA: A Decision Support System for the Construction of Cattle Diets.- Prediction of Parthenium Weed Dispersal Using Fuzzy Logic on GIS Spatial Image.

The helicopter fuselage has the characteristics of compact structure space, complex coordination relationship and weak rigidity, etc. It is difficult to control the accuracy of the desired shape. According to the high precision and quality requirement of final assembly for helicopter fuselage, the application status of automatic assembly technology in aviation manufacturing was analyzed. Then the difficulties of automatic assembly technology for fuselage final assembly were also discussed. In this paper, an automatic assembly system for the final assembly of helicopter fuselage was designed, and relevant key technologies of the assembly system mentioned above were proposed. The designed system have the functions of automatic positioning, clamping, measuring, drilling, feeding and blind fastener riveting for fuselage components, which can improve the assembly quality and efficiency of helicopter fuselage during the final assembly process.

Product development decisions represent challenging processes with various stakeholders from different disciplines and with different perspectives involved. Decisions can be highly complex due to the high amount of influencing factors that have to be considered simultaneously. Among other methods and tools, decision support systems (DSS) were developed to support decision-makers in handling complex decisions. One main disadvantage of DSS is the little adaptation to and integration of decision-maker needs and characteristics. Thus, current trends focus on the development of human- and decision-maker-centered DSS. This paper aims in providing a multilevel stepwise procedure for the modeling of decision-makers in order to enable a more effective decision support. The decision-maker modeling procedure is based on findings from literature research and results from research projects performed in cooperation with industry partners. The procedure serves as a guideline for generating diverse decision-maker models for different applications and for integrating human cognitive thinking procedures within the design and functionality of decision support methodologies and systems. The procedure represents an important design element of the human-centered decision support methodology currently being developed at the Institute of Product Development of the Technische Universität München (Germany).

A statistical method for improving the accuracy of predictive mathematical models used in drilling operations is proposed. The scheme can be applied in drilling automation, for example for improving accuracy in automated control systems such as managed pressure drilling (MPD), and for more reliable real-time monitoring and decision support systems. The proposed method is applied to a simulated case of MPD. Hydraulic model predictions of BHP are continuously compared to PWD readings. A short sequence with varying pump rate is run to train the statistics, which are collected at each pump rate, and refined considering also the pump rate derivative. This is visualized as a 3D surface giving a clear illustration of the error signature of the simulated case. The estimated error is added to the set point of the choke control system, demonstrating a clear improvement of BHP control. We proposed a new statistical method that uses real-time sensor data to perform automatic fingerprinting of the predictive performance of a given model. The principle is simple but powerful and can be applied to many cases. It can be combined with smart visualization tools in decision support systems, helping to build confidence in the users, or even utilized to adjust the initial prediction for improved accuracy in control systems. The tool is independent of the internal calculations in the mathematical model, and it can therefore be utilized in combination with any model.

PurposeThe purpose of this paper is to design a new method to realize automatic assembly of aircraft components with large shafts such as canard and vertical tail. The assembly structure of component with large shaft and fuselage is a mating assembly structure, and it is a challenge to satisfy the precision and assembly requirement.Design/methodology/approachAccording to the assembly structure features and process requirements of an aircraft component with large shaft, the operating principle of precise assembly system for shaft-hole mating is analyzed in this paper. The model of compliant assembly for shaft-hole mating is constructed, and force condition analysis of the compliant assembly is performed. An automatic precise shaft-hole assembly method for aircraft assembly using 5 degrees of freedom spatial mechanism, compliance technology and servo feeding system is put forward based on the analysis. A 5 degrees of freedom passive compliant experimental equipment has been developed.FindingsApplication test results of the 5 degrees of freedom passive compliant experimental equipment show that the simulated canard can be mated automatically and accurately through this method with high efficiency and high quality as long as the tip of shaft enters into the range of hole’s chamfer.Practical implicationsThis method has been used in an aircraft assembly project. The practical results show that the aircraft components with large shafts can be mated automatically and accurately through this method with high efficiency and high quality.Originality/valueThis paper presents a new method and designs a new assembly system to realize the assembly of the aircraft components with large shafts. The research will promote the automation of fuselage assembly.

This paper aims to introduce the Decision Support System (DSS), which is an area informatics approach to area studies, and the research network complex based on DSS's application in Thailand. In particular, the paper presents and discusses current activities of the DSS research network at the national level in Thailand rather than being a theoretical and analytical study of the DSS mechanism or its cases. DSS has wide applications in Thailand, extending to various fields such as agricultural and natural resource management, economic and social management, historical and cultural preservation, and so on. DSS generally refers to a support system embedded into a computer system for providing intellectual resources with the appropriate numerical model necessary for decision making in production activities. Agricultural and natural resources have been the foundation of social and economic development in Thailand since the country's first national plan in the1960s. Decision making to maintain agricultural productivity as well as to protect natural resources requires well-integrated data sets. The Thailand Research Fund(TRF) established a DSS research and development network (TRF-DSS) in 2002 to help various research teams in Thailand develop DSS tools and components for addressing agricultural and natural resource management issues. Using a "systems"approach, the DSS framework allows researchers and users to identify and integrate key components as well as to define databases and model-base management systems. This paper focuses on the TRF-DSS research and development network, which consists of 12 universities, two line agencies in Thailand, and a line agency in Cambodia. During 2002–10, a total of 59 research projects were granted a budget allocation of 140.1 million baht, and a budget of 15.4 million baht was allocated to support activities of the network. In addition, 10 projects were funded to carry out post-project activities, with a total budget of 1.5 million baht. More than 20 DSS tools were developed and implemented by various users, ranging from policy makers to provincial and local government agencies engaged in short- and long-term planning and management. Most DSS tools were designed to allow the integration of biophysical and socioeconomic data as well as the decision support modules for alternatives evaluation and analysis. These approaches support the choices of dynamic simulation models as well as multi-criteria analyses for modelbase software development. They also allow users to evaluate various alternatives in agricultural and natural resource management. Networking is a powerful platform for DSS research and development and maybe applied to other types of research and development agenda in Thailand, such as area study projects. DSS tools contribute to an understanding of sustainability of production systems against a background of climate change, poverty reduction, and food security.

Integrated pest management (IPM) prioritizes non-chemical alternatives for managing pests and/or diseases, reserving chemicals as last solution, when economically and environmentally justified. The holistic consideration of the agroecosystem makes decision-making in crop protection more complex, as it requires selecting the most appropriate action at the right time. Decision support systems (DSS) for IPM help manage the risks of pests and diseases affecting crops by predicting potential threats and suggesting suitable control measures. However, their adoption remains modest among farmers, despite demonstrated benefits. An anonymous online survey was conducted among farmers, advisors, and other agricultural stakeholders to investigate factors influencing DSS uptake, or lack thereof. The survey distinguished between DSS users and non-users, enabling targeted questions on different aspects of DSS use and adoption. In total, 78 respondents were classified as DSS users and 29 as DSS non-users . Data were analyzed through clustering, followed by statistical validation of clusters and induction of a classification tree, to identify the most influential features shaping cluster formation among both DSS users and DSS non-users . The analysis identified four clusters in the DSS users’ dataset and two clusters in the DSS non-users’ dataset. For DSS users , DSS output reliability and usefulness were identified as the most influential features. Membership in a farmers’ network and DSS ease of use also contributed to cluster separation. For DSS non-users , DSS availability for different cropping systems was the most important attribute determining cluster separation. The results indicate that farmer involvement in DSS development and calibration may enhance trust and, therefore, adoption. Moreover, the need for user-friendly systems providing simple and clear information was highlighted. Although the lack of DSS tailored to specific cropping systems emerged as the main barrier, limited awareness and concerns about costs were also important obstacles. The applied methodological approach presents a reproducible and robust AI-based framework, built on open-source tools, to analyze stakeholders’ perceptions of IPM DSS and extract knowledge from complex survey data. This study provides valuable insights to facilitate DSS adoption for more sustainable crop protection and underscores the importance of both DSS technical performance and end-user needs.

Our latest research has shown that in order to be able to develop and maintain different final assembly systems and to further develop industrial work, the introduction of new types of product structures is a necessity. At the same time these new structures allow resistant relationships to be found as a basis for orientation, to exploit to a greater extent than previously the precise work of the design department in central pre–production and the various final assembly processes. This is possible in the motor vehicle industry since automobiles and trucks display certain generic characteristics. The consequence is that the information systems in use today and the company's transfer surfaces within the internal organization must be changed, which presupposes new types of product structures. This is especially important when the new long cycle assembly work is realized. This paper summarizes some experience and methods from the development of long cycle time assembly systems, and reports general questions valid for the person or the company intending to humanize and make assembly work more efficient, and illustrates these questions with specific 'delimited' examples. Here we refer principally to the development of ways of describing products. Our results are based on several years' collaboration, characterized as action research, between researchers and practitioners mainly within the Volvo Car and Volvo Truck Corporations. The work has led to real implementation of research results in industrial environments. When designing alternatives to traditional line–assembly, we advocate a generally applicable product structure as a basis, which is then adapted to different local final assembly plants. When this approach is used it has proved to be important to define principles of differentiation between causal and taxonomic descriptions and the use of stereometric models of products and local assembly processes in relation to central design and pre–production departments is essential. In this paper, we report a number of practical examples to illustrate the empiric support for the reasoning applied, and these in turn have necessitated certain modifications to the original basic stereometric model that we have published previously. These modifications are also based on practical experience which is not explicitly reported in this paper.

Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS) is an algorithm that can be used for alternative design in a decision support system (DSS). TOPSIS provides recommendation so that users can get information that support their decision, for example a tourist wants to visit a tourist destination in Malang, then TOPSIS provides recommendations of tourist destinations in the form of ranking recommendation, with the highest rank is the most recommended recommendation. TOPSIS-based Mobile Decision Support System (DSS) has relatively low algorithm complexity. However, there are some cases that require development from personal DSS to group DSS, for example tourists rarely come alone, in which case most of them invite friends or family. For users who are more than 1 person, the TOPSIS algorithm can be combined with the BORDA algorithm. This study explains about the implementation & testing of TOPSIS and TOPSIS-BORDA as algorithms for personal and group DSS in mobile-based tourism recommendation system in Malang. Correlation testing was conducted to test the effectiveness of TOPSIS in mobile-based recommendation system. In previous study, correlation testing for personal DSS showed that there was a relationship between the recommendation and user choice, with correlation value of 0.770769231. In this study, correlation testing for group DSS showed there is a positive correlation of 0.88 between the recommendations of the group produced by TOPSIS-BORDA and personal recommendations for each user produced by TOPSIS.

Changing systems for supporting farmers' decisions: problems, paradigms, and prospects

Nowadays, regardless of the popularity and credibility of Decision Support Systems (DSS), measuring the efficacy of the decisions taken by the DSS is yet to be proven. As previous works identifies the complexities involved in measuring the efficiency of DSS, most of the time DSS efficiency is case dependent. The list of methods for collecting and analyzing data, building models, deployment models, data and model integration, and finally taking decisions are some of the major issues related to measuring DSS effectiveness. This paper focuses on measuring the effectiveness of DSS. The paper highlights the issues that still need to be addressed with efficient frameworks. Based on the literature review and discussion presented in Section I and II, this study proposed a framework and its implementation. Presents how the proposed model can improve the previous work. The major findings of this study reflect that every decision made by DSS is based on the collected data, analyzed by DSS tools, as well as depends on the developed models. Therefore, this study illustrated that each component of DSS plays vital role in measuring the effectiveness of DSS whatever the case and problem for which the DSS has been built and implemented for. In addition, the supporting methods and measuring factors for each component are other findings of this study. Any decision taken by DSS will be evaluated separately in order to measure the effectiveness of the system. The proposed framework resembles a new framework for the decision makers working in any industry.

ObjectiveThe study investigates users’ tendency to access decision support (DS) systems as a function of the correlation between the DS information and the information users already have, the ongoing interaction with such systems, and the effect of correlated information on subjective trust.BackgroundPrevious research has shown inconclusive findings regarding whether people prefer information that correlates with information they already have. Some studies conclude that individuals recognize the value of noncorrelated information, given its unique content, while others suggest that users favor correlated information as it aligns with existing evidence. The impact of the level of correlation on performance, subjective trust, and the decision to use DS remains unclear.MethodIn an experiment (N = 481), participants made classification decisions based on available information. They could also purchase additional DS with different degrees of correlation with the available information.ResultsParticipants tended to purchase information more often when the DS was not correlated with the available information. Correlated information reduced performance, and the effect of correlation on subjective trust and performance depended on DS sensitivity.ConclusionAdditional information may not improve performance when it is correlated with available information (i.e., it is redundant). Hence, the benefits of additional information and DS depend on the information the system and the operator use.ApplicationIt is essential to analyze the correlations between information sources and design the available information to allow optimal task performance and possibly minimize redundancy (e.g., by locating sensors in different positions to capture independent data).

BackgroundTranslating scientific evidence into daily practice is problematic. All kinds of intervention strategies, using educational and/or directive strategies, aimed at modifying behavior, have evolved, but have been found only partially successful. In this article the focus is on (computerized) decision support systems (DSSs). DSSs intervene in physicians' daily routine, as opposed to interventions that aim at influencing knowledge in order to change behavior. We examined whether general practitioners (GPs) are prescribing in accordance with the advice given by the DSS and whether there is less variation in prescription when the DSS is used.MethodsData were used from the Second Dutch National Survey of General Practice (DNSGP2), collected in 2001. A total of 82 diagnoses, 749811 contacts, 133 physicians, and 85 practices was included in the analyses. GPs using the DSS daily were compared to GPs who do not use the DSS. Multilevel analyses were used to analyse the data. Two outcome measures were chosen: whether prescription was in accordance with the advice of the DSS or not, and a measure of concentration, the Herfindahl-Hirschman Index (HHI).ResultsGPs who use the DSS daily prescribe more according to the advice given in the DSS than GPs who do not use the DSS. Contradictory to our expectation there was no significant difference between the HHIs for both groups: variation in prescription was comparable.ConclusionWe studied the use of a DSS for drug prescribing in general practice in the Netherlands. The DSS is based on guidelines developed by the Dutch College of General Practitioners and implemented in the Electronic Medical Systems of the GPs. GPs using the DSS more often prescribe in accordance with the advice given in the DSS compared to GPs not using the DSS. This finding, however, did not mean that variation is lower; variation is the same for GPs using and for GPs not using a DSS. Implications of the study are that DSSs can be used to implement guidelines, but that it should not be expected that variation is limited.