A Combined Multicriteria Approach for Cellular Manufacturing Layout

Quantitative and Qualitative Ultrasound Evaluation for the Diagnosis of an Anterosuperior Acetabular Labral Tear.

This paper is directed toward the development of models, methods and tools suitable for effective, profitable, and autonomous cellular manufacturing as a new vision for 21st Century. The cellular manufacturing is mainly concerned with the efficient integration of three major concerns : (1) planning-oriented predictive cellular layout design; (2) an unexpected order-adapted cellular manufacturing through the integration between manufacturing decision processes and cellular layout, and (3) a contingency-driving shop floor adaptation for supporting continuous improvement. The system supports the user with five modules : real-time status monitoring, data acquisition and analysis, diagnosis through intelligent decision support system, simulation optimization, and results evaluation and performance measurement.

The formation of machine–part families is an important task in the design of cellular and flexible manufacturing systems. The formation results in the creation of many benefits for manufacturing systems. Among the many methods utilised in machine–cells formation, the similarity coefficient method (SCM) is most widely used. When SCM is used, the rearrangement of machine and part components is required to form machine–part families. This process of rearrangement has been considered as being subjective and difficult, may result in improper assignments to parts families, resulting in a negation of benefits promised. This paper presents an effective algorithm to identify part–families and bottleneck parts, given machine groupings, rather than addressing the machine grouping problem in general.

To develop an optimized interpretation strategy of dynamic contrast enhanced breast MRI based on a combination of quantitative and qualitative criteria, the features of 120 histopathologically verified lesions were retrospectively analysed on contrast enhanced dynamically acquired (before and 1, 2, 4 and 7 min following injection of 0.2 mmol kg-1 gadolinium-DOTA) three-dimensional gradient echo images. Quantitative criteria, based on relative signal intensity measurements and qualitative morphological features, including lesion shape, margins and enhancement patterns were analysed in regard to differentiating malignant (n = 70) from benign (n = 50) lesions. Quantitative assessment of enhancement profiles was most accurate when analysis was based on early 1 min measurements. Using a 90% threshold, sensitivity and specificity in detecting breast cancer were 83% and 66%, respectively. When based on qualitative morphological analysis alone, sensitivity and specificity were 83% and 54%. Combined quantitative and qualitative assessment yielded a considerably higher sensitivity, specificity and accuracy of 93%, 74% and 85%, respectively. In conclusion, results from dynamic contrast enhanced breast MRI can be improved by basing the interpretation on both quantitative and qualitative criteria.

This paper focuses on the sorting problems with multiple types of attributes. About the attributes, in which are divided into qualitative attributes, quantitative attributes, qualitative criteria and quantitative criteria. Granules of knowledge are defined by applying four types of relations simultaneously: indiscernibility relation defined on qualitative attributes, similarity relation defined on quantitative attributes, dominance relation defined on qualitative criteria and quasi-partial order relation defined on quantitative criteria. To guarantee the tolerance of the system, the threshold is adjusted, resulting in a N-neighborhood system comes into being. The consistency measure which possess properties of monotonicity is regarded as the Likelihood Function, so the optimal threshold is obtained by Maximum Likelihood Estimation, as a result, N-neighborhood system is converted into optimal 1-neighborhood system. Therefore, we proposed the Optimal-Neighborhood Statistics Rough Set Approach with Multiple Attributes and Criteria.

This paper uses fuzzy sets and fuzzy numbers to reduce the subjectivity in the assignment of qualitative criteria in a design problem. Through fuzzy measures and the Choquet integral it is possible to combine multiple qualitative and quantitative criteria into a single numerical value and make a proper design decision. The fuzzy measures, indicators of the importance of single criteria are determined using a linear program optimization method. The input for the linear program is only a preference order of some of the alternatives. With the verified fuzzy measures it is then possible to compute a single numerical value for the remaining alternatives. This results in an order of preferred design constructions and a recommendation for an optimized design. The theory is applied to EEGIEOG (electroencephalography/electrooculography) electrode placement for sleep monitoring by incorporating the criteria: comfort, reliability and power consumption.

Cellular manufacturing (CM) is now an established international practice to integrate: equipment, people, and systems into 'focused factories', 'mini-businesses' or 'cells' with clear customers, responsibilities and boundaries. The major element in exploiting the benefits of CM is efficient layout designs. In this paper, problem of machine assignment is considered in a cellular layout. The focus is on the intra-cell machines allocation, because the inter-cell material flows should be minimal in CM. The modified artificial bee colony (MABC) algorithm is proposed to solve the layout problem. The algorithm tackles one cell at a time with a maximum of nine machines, which will be assigned into a 3 × 3 grid space according to the ranking result. This problem involves five parts and five quantitative demand periods are considered. To examine the performance of the proposed MABC, datasets are taken from the literature and the results are compared with those of other approaches. The proposed MABC provides an optimal layout exactly.

International Engineering Consortium predicted that cellular manufacturing would become the main production model of manufacturing enterprises in the future. In recent years, studies both at home and abroad were primarily around cellular manufacturing system design and equipment layout, while research on cellular manufacturing management pattern was relatively small. Based on elaborating the basic concepts and organizational forms of cellular manufacturing, this paper gives autonomous management models of cellular manufacturing, and proposes optimization management method, so as to expand production management theory and provide reference to cellular manufacturing enterprises.

Knowledge is one of the most precious resources of an organization. Every organization wishes to preserve and fully utilize its knowledge. Within organization knowledge is present in various forms, may be in the minds of workers or in documented form. In documented form the knowledge has various representation schemes such as frames, scripts, lists, decision trees and decision tables etc. We have proposed a transformation method to optimally transform knowledge present in decision trees and decision tables into knowledge base. According to our proposal, the knowledge present in these two representation schemes should first be converted into corresponding set of human interpretable rules by using some existing transformation algorithms. The decision tree should be converted directly into set of human interpretable rules but for decision table transformation, two ways are adopted; either it should be converted first into decision tree and then to set of rules or, should be converted directly into set of rules. Once the set of rules is obtained then it will be optimized by using some existing optimization algorithms and unnecessary conditions will be omitted. After rules optimization process, comparison with the existing rules in the knowledge base is carried out. If these optimized rules are not found in the knowledge base, it should be added. If some rules need updation, then these should be added after updation. During comparison those rules which already exist in the knowledge base should be omitted.

Most of the garment productions line behaves as one entity, empowerment, and team work are complicated to be promoted. Most of garment firms are international export oriented earnings in Tirupur. It plays an important contribution to state government budget. Weightless machines are needed to produce the garments in selected industry which is effortless to implement cellular manufacturing design layout. By implementing lean design and implementation of a valuable team work concept and cellular manufacturing layout design in selected garment firm to reduce motion of employee during working hours, defects of garment items and proper utilization of employee for achieving more earnings. This research article address the implementation of design of cellular manufacturing layout and a valuable team work concept in selected garment manufacturing firms.

While evaluating and selecting investment projects, modern companies are confronted with the problem of setting priorities between profitability and riskiness of these projects. Choice of a project on the basis of its profitability significantly increases risks of financial and economic activities and decreases the certainty of achieving the planned financial result. On the other hand, attempts to decrease investment projects risks may not allow one to achieve the desired profitability level. Therefore, it is vital to develop integrated multi-criteria indicators for this purpose. This article is the result of the authors’ development of an integral indicator for evaluating investment project efficiency and risks. The developed integral indicator has a matrix form. To compile the integral indicator, three groups of criteria are used: quantitative efficiency criteria, qualitative efficiency criteria and risk evaluation criteria. We propose to divide the qualitative and quantitative criteria into: 1) those defining the commercial (economic) efficiency of projects, 2) those defining their budgetary efficiency; 3) those defining their social efficiency. According to the authors, the list of criteria that define associated risks should include macroeconomic indicators and industry affiliation indicators that provide a comprehensive evaluation of the external economic situation on the corresponding market. While evaluating efficiency and riskiness of the given projects, the integral indicator developed by the authors is converted from matrix form into a quantitative indicator that is easy to interpret. The authors propose to use principal component analysis and heuristic methods (including ranking method and hierarchy analysis method) for this purpose. The results of this research can be used by companies to select investment projects.

Impact or risk assessments of alien species can use qualitative criteria (such as verbally described categories) or quantitative criteria (numerically defined threshold values of empirically measurable quantities). According to a common misconception, the use of qualitative criteria in invasion biology is justified by uncertainty in the available data. Yet qualitative criteria have the effect of increasing uncertainty. In contrast, assessments using quantitative criteria are testable, transparent, highly repeatable and comparable. Most of these characteristics do not even depend on the availability of numerical data. Although quantitative criteria do not necessarily make assessments correct, they do make them correctable, which is the benchmark of science.

Most of the techniques for the cell design (CD) problem in cellular manufacturing (CM) consider only the machine-part incidence matrix as the input. They then convert this matrix into a block diagonal form to create a dedicated and independent cell for each part family, without laying out machines. Yet due to the lack of information on the layout, hence the lack of information on the performance of the shop floor, the benefits of CM cannot be validated. Furthermore, operational issues, e.g. scheduling, have an effect on the CD. However, current techniques are not comprehensive enough for a complete CD which should consider the aforementioned issues as a whole. This paper proposes a two-phase method based on total manufacturing lead time (MLT) reduction to overcome these drawbacks. In the first phase, the system is simulated by considering all of the operational issues under the assumption of zero material handling times to minimize total MLT. Besides minimized total MLT, the first phase also yields the waiting times of parts and the volume of the parts-flow between machines, which are used to find similarity measures between machines in the second phase. The second phase then exploits an algorithm which creates and uses these similarity measures to construct a layout by locating machines with higher similarity next to each other to justify the assumption of minimal total MLT and to minimize total material handling time.

A simulation based experimental design to analyze factors affecting production flow time

Cellular manufacturing is a lean manufacturing approach that involves grouping machines, processes, and workstations into self-contained cells to reduce material handling, waiting times, and inventory. The layout design of cellular manufacturing facilities has a significant impact on their efficiency, productivity, and throughput. However, traditional trial-and-error methods for facility layout design can be time-consuming, costly, and risky. Digital twin simulation offers a powerful alternative by allowing designers to create virtual models of the facility and test different layout configurations before physically implementing them. Our study shows that digital twin simulation can help identify the optimal layout design that maximizes productivity, minimizes waste, and ensures the smooth flow of materials and products. Additionally, it enables us to evaluate the impact of changes in the production system on the facility's performance, helping decision-makers make informed decisions. Overall, this paper highlights the potential of digital twin simulations as a powerful tool for optimizing cellular manufacturing facility layout design and improving operational performance.