Cell formation using multiple process plans

Cell formation (CF) consists of identifying machine groups and part families. Many CF procedures use a part machine matrix as an input and attempt to obtain a block diagonal form. But perfect block diagonalization of parts and machines is not possible is many cases. In this paper we consider a generalized cellular manufacturing (CM) problem, in which each part can have alternate process plans and each operation can be performed on alternate machines. Under these conditions the CF problem of assigning parts and machines to each manufacturing cell can be considered as a two stage process. The first stage deals with the problem of determining a unique process plan for each part. The second stage determines the part families and machine cells. In this research a model for forming part families and machine cells is presented considering alternate process plans. The objective is to analyze how alternate process plans influence and enhance the CM process giving better flexibility to the designer while designing cells for CM.     

Texture Pattern Generation Using Clonal Mosaic Texture Pattern Generation Using Clonal Mosaic

In this paper, an effective system for synthesizing animal skin patterns on arbitrary polygonal surfaces is developed. To accomplish the task, a system inspired by the Clonal Mosaic （CM） model is proposed. The CM model simulates cells＇ reactions on arbitrary surface. By controlling the division, mutation and repulsion of cells, a regulated spatial arrangement of cells is formed. This arrangement of cells shows appealing result, which is comparable with those natural patterns observed from animal skin. However, a typical CM simulation process incurs high computational cost, where the distances among ceils across a polygonal surface are measured and the movements of cells are constrained on the surface. In this framework, an approach is proposed to transform each of the original 3D geometrical planes of the surface into its Canonical Reference Plane Structure. This structure helps to simplify a 3D computational problem into a more manageable 2D problem. Furthermore, the concept of Local Relaxation is developed to optimally enhance the relaxation process for a typical CM simulation. The performances of the proposed solution methods have been verified with extensive experimental results.     

A meta-heuristic algorithm to solve quadratic assignment formulations of cell formation problems without presetting number of cells

The purpose of cellular manufacturing (CM) is to find part-families and machine cells which form self-sufficient units of production with a certain amount of autonomy that result in easier control (Kusiak, 1987, 1990). One of the most important steps in CM is to optimally identify cells from a given part-machine incidence matrix. Several formulations of various complexities are proposed in the literature to deal with this problem. One of the mostly known formulations for CM is the quadratic assignment formulation (Kusiak and Chow, 1988). The problem with the quadratic assignment based formulation is the difficulty of its solution due to its combinatorial nature. The formulation is also known as NP-hard (Kusiak and Chow, 1988). In this paper a novel simulated annealing based meta-heuristic algorithm is developed to solve quadratic assignment formulations of the manufacturing cell formation problems. In the paper a novel solution representation scheme is developed. Using the proposed solution representation scheme, feasible neighborhoods can be generated easily. Moreover, the proposed algorithm has the ability to self determine the optimal number of cell during the search process. A test problem is solved to present working of the proposed algorithm.     

A productivity measurement model using a programmable calculator

A comprehensive total factor productivity measurement model has been developed by the American Productivity Center for use in firm-level and plant-level productivity measurement. The computer program for this model is available from the APC in Houston, Texas for use on a main-frame computer system. However, this model has now been programmed for use on a Texas Instruments TI-59 programmable calculator with a PC-100 printer. This makes possible several inexpensive applications of the model, including the use of the model for small business with limited computer availability, use by consultants for developing complex measurement systems, and for training purposes in the application of the model and analysis of results. The article describes total factor productivity, discusses the APC model, and presents the program listing and operating instructions for the programmable calculator version of the model.     

EFFECTIVENESS,PRODUCTIVITY AND DESIGN OF PURPOSEFUL SYSTEMS: THE PROFIT-MAKING CASE,

Abstract

A generalized goat attainment model or effectiveness is presented and a measure of system effectiveness which indicates how close a technology comes to delivering operational goals Is developed. The operational goals themselves arc defined In relation to underlying values. The effectiveness measure Is then related to system efficiency (itself one effectiveness goal but also a determinant of effectiveness) measured here by total factor productivity. Improved system efficiency (productivity) control can result in an increase in effectiveness thereby facilitating goals/values adaptation. Two examples of this interaction are provided.     

Performance analysis of assembly systems with highlift stations: a practical approach

One common problem associated with automatic assembly systems is that some assembly operations may have relatively long cycle times. As a consequence, the productivity, as determined by the operations with the longest cycle time, can be significantly reduced. Therefore, a special form of parallel workstation known as a highlift station was developed to improve the performance of an automatic assembly system. In this paper, we present a simple analytical model that can help engineers to estimate the performance of highlift stations. This model is particularly useful at the design stage, as only approximate results are necessary for selecting the configuration.     

Design of virtual manufacturing cells: a mathematical programming approach

In this paper, a new type of virtual cellular manufacturing (CM) system is considered, and a multi-objective design procedure is developed for designing such cells in real time. Retaining the functional layout, virtual cells are addressed as temporary groupings of machines, jobs and workers to realize the benefits of CM. The virtual cells are created periodically, for instance every week or every month, depending on changes in demand volumes and mix, as new jobs accumulate during a planning period. The procedure includes labor grouping considerations in addition to part-machine grouping. The procedure is based on interactive goal programming methods. Factors such as capacity constraints, cell size restrictions, minimization of load imbalances, minimization of inter-cell movements of parts, provision of flexibility, etc. are considered. In labor grouping, the functionally specialized labor pools are partitioned and regrouped into virtual cells. Factors such as ensuring balanced loads for workers, minimization of inter-cell movements of workers, providing adequate levels of labor flexibility, etc. are considered in a pragmatic manner.     

Growing RBFNN-based soft computing approach for congestion management

In the emerging restructured power system, the congestion management (CM) has become extremely important in order to ensure the security and reliability of the system. In addition to this, lack of CM can impose a hindrance in electricity trading. This paper presents a novel, growing radial basis function neural network (GRBFNN)-based approach for CM. For achieving CM, Nodal congestion price (NCP) forecasting is performed in real time competitive power market. NCP forecasting is an effective way of price-based preventive CM as it directly indicates the presence as well as the severity of the congestion in the system. In present paper, GRBFNN has been developed for NCP forecasting dividing the whole power system into various congestion zones. An unsupervised learning vector quantization (VQ) clustering algorithm is applied as feature selection technique for the developed GRBFNN and for partitioning the power system into different congestion zones. For each congestion zone a separate neural network has been developed to ensure faster training and accurate forecasting results. The proposed approach of CM is implemented on an RTS 24-bus system. The results obtained are compared with a different constructive algorithm-based RBF network called as general regression neural network (GRNN) and two back-propagation algorithms based ANNs. Comparison results show that proposed GRBFNN is more computationally efficient with better predictive ability.     

Effect of the identification of key machines in the cell formation problem of cellular manufacturing systems

Cellular manufacturing as been viewed as an important manufacturing philosophy that has helped both small and medium sized parts manufacturers increase their manufacturing productivity. In the analysis of a cellular manufacturing problem, identifying the key machines representing the manufacturing cells is an important step in the determination of final part-machine clusters. Three different methods have been proposed in this paper for performing this identification, and a more complete model taking into consideration the sequence of operations exhibited by parts have been developed for minimizing total moves. The total movefs contributed by all parts have been evaluated as a weighted sum of both inter- and intracell moves. A heuristic solution algorithm developed for the model has been operationalized by implementing the associated computer program on an IBM PC compatible microcomputer. The sensitivity of each of the three proposed methods with regard to identifying the key machines and their impact on the selection of final part-machine clusters has been analyzed by solving an example problem. The results obtained show that method 2 outperforms the other two (methods 1 and 3) in determining the best part-machine clusters in cellular manufacturing, thus making it a better decision tool to be used by both small and medium sized parts manufacturers in production planning.     

Invention principles and contradiction matrix for semiconductor manufacturing industry: chemical mechanical polishing

The classical contradiction matrix (CM) and inventive principles (IPs) developed by Altshuller were based on patents from traditional industries in the 1950s. Evidences showed that the classical contradiction matrix and inventive principles are not quite suitable for newer hightechnology industries such as semiconductor industry due to the fact that the fundamental physics of operating principles are different. To date, no research has developed any CM and IP specifically suitable for the semiconductor industry. This research, as the first step of efforts develop to suitable CM and IP for semiconductor industry using patents from Chemical Mechanical Processing (CMP) equipment and processes in the semiconductor industry. By focusing on a particular industry, we can develop a more suitable CM and IP for that particular industry and with less number of patents needed to review. The results show that a newly established preliminary CM based on merely 120 patents from 1999 to 2008 can interpret 80% of the inventive principles in a set of new patents. This is a significant improvement over the original Altshuller’s original CM which can only interpret 40% with 40,000 patents studied. In addition, during this study, two existing principles were revised to reflect a broader application and three new inventive principles were identified. The contributions of this research include: 1) Revising the traditional engineering parameters to be consistent with semiconductor industry including the addition of 7 new parameters; 2) Identifying 3 new IPs and modifying 2 IPs for CMP processes; 3) Establishing a triplet representation to model any patent to facilitate future analytical studies of the contradiction matrix and IPs.     

Robot-process precision modelling for the improvement of productivity in flexible manufacturing cells

Industrial robots are traditionally used at machining cells for machine feeding and workpiece handling. A reassignment of tasks to improve the productivity requires a modelling of the robot behaviour from the point of view of its position precision. This paper characterizes and predicts the precision achievable when drilling with an industrial robot in order to use it in machining operations.Robot behaviour and drilling phenomena are analysed to determine working accuracy and their contribution in position deviation and uncertainty. An efficient model for drilling is developed, applying quaternions and considering the influence of all cutting tool angles, providing a very precise estimation of drilling torques and forces. An innovative model for the robot is developed based on multibody systems, using mixed natural coordinates that enhance the computing and deliver outputs with direct interpretation. Besides, the effect of stiffness is added in joints as additional element.The complete robot-process model shows the significative process influence in working precision against robot influence. This influence is responsible of up to 40% of the total uncertainty. The model and the tests performed show that the deviations and their uncertainties depend strongly on drilling forces and the robot configuration. In the other hand, the model allows to correct the systematic behaviour in robot deviations and improve with that the position tolerance of the holes to be drilled.     

An efficient heuristic for reliability design optimization problems

This paper develops an efficient heuristic to solve two typical combinatorial optimization problems frequently met when designing highly reliable systems. The first one is the redundancy allocation problem (RAP) of series-parallel binary-state systems. The design goal of the RAP is to select the optimal combination of elements and redundancy levels to maximize system reliability subject to the system budget and to the system weight. The second problem is the expansion-scheduling problem (ESP) of multi-state series-parallel systems. In this problem, the study period is divided into several stages. At each stage, the demand is represented as a piecewise cumulative load curve. During the system lifetime, the demand can increase and the total productivity may become insufficient to assume the demand. To increase the total system productivity, elements are added to the existing system. The objective in the ESP is to minimize the sum of costs of the investments over the study period while satisfying availability constraints at each stage. The heuristic approach developed to solve the RAP and the ESP is based on a combination of space partitioning, genetic algorithms (GA) and tabu search (TS). After dividing the search space into a set of disjoint subsets, this approach uses GA to select the subspaces, and applies TS to each selected subspace. Numerical results for the test problems from previous research are reported and compared. The results show the advantages of the proposed approach for solving both problems.     

Anomaly detection and critical attributes identification for products with multiple operating conditions based on isolation forest

Performance analysis of the existing mechanical products is critical to identifying design defects and improving product reliability. With the advances of information technologies, product operating data collected through continuous condition monitoring (CM) serve as main sources for analysis of performance and detection of anomaly. Most of the existing anomaly detection methods, however, are not effective when CM data are very high dimensional, leading to poor quality of assessment results. Besides, the effects of multiple operating conditions on anomaly detection are seldom considered in these existing methods. To solve these problems, an integrated approach for anomaly detection and critical behavioral attributes identification based on CM data is developed in this research. Gaussian mixed model GMM) is employed to develop a method for clustering of operating conditions. Isolation forest (iForest) method is used to detect anomaly instances, and further to identify the critical attributes related to product performance degradation. The effectiveness of the developed approach is demonstrated by an application with collected operating data of a wind turbine.     

Data flow model of a total service quality management system

A total service quality management model was developed in this paper. The design integrated the pre-service delivery stage, service delivery stage and post-service delivery stage into one single model, similar to the structure of a total manufacturing quality management system. The design specification was described by means of data flow diagrams (DFD). The model can be used as the base for further development toward a computer integrated service quality management information system.     

Forecasting plant labor productivity with a time series model

Plant labor productivity index, defined as the ratio of the standard labor hours and actual labor hours, is an important factor in the determination of the future manpower needs at Cessna Aircraft Co. (Pawnee Division). In this paper, a time series model based on the Box-Jenkins modelling approach is developed. A greater accuracy in forecasting future labor productivity index has been achieved by using this model.     

Study on the assembly and separation of biological cell by optically induced dielectrophoretic technology

Optically induced dielectrophoretic (ODEP) chip is to combine their own advantages of optical tweezers and electrodynamics manipulation technologies, which can trap single particles in high resolution as well as enrich much of micro-/nanoparticles in high throughput. The paper analyzed the structure of optoelectronic tweezers (OET) chip, moreover, the frequency response of multi-membrane eukaryotic cells about 10³–10⁹ Hz. The Clausius–Mositti (CM) frequency factor in terms of cell membrane, cell cytoplasm, nuclear envelope thickness changes, and volume ratio was illustrated. In the end, the paper presented 3D numeric model of cells in OET chip. The dielectrophoresis force acting on the dipole of 11.8-μm cells subjected to a non-uniform electric field under 60-μm Gaussian-distributed beam spot could be simulated in the enrichment process. The separation of cells that were two different types of CM values was calculated. Furthermore, it was proved to be feasible to achieve the efficient separation of cells using ODEP technology in the biological numerical model. Comparing with the literature of experiment, the results in cell dielectric spectroscopy and numeric model findings were in general agreement. The simplified structure and numeric model of nucleated cell provide a theoretical basis for research of biosensor and complex life.     

多关节柔性三坐标测量系统误差分析研究

为了克服传统三坐标测量系统的体积大、结构复杂、不能现场测量等缺点,研制开发一种新颖的基于旋转关节和转动手臂的多关节柔性三坐标测量系统.首先基于Denavit-Hartenberg方法建立了多关节柔性三坐标测量系统的理想数学模型,在考虑到结构误差基础上修正得到误差模型,最后详细分析系统中影响测量结果的各种误差因素.仿真实验结果表明数学模型的正确性,并为进一步研究系统的误差补偿和提高测量精度提供了理论基础.     

A comparison of concurrent programming and cooperative multithreading under load balancing applications

Two models of thread execution are the general concurrent programming execution model (CP) and the cooperative multithreading execution model (CM). CP provides nondeterministic thread execution where context switches occur arbitrarily. CM provides threads that execute one at a time until they explicitly choose to yield the processor. This paper focuses on a classic application to reveal the advantages and disadvantages of load balancing during thread execution under CP and CM styles; results from a second classic application were similar. These applications are programmed in two different languages (SR and Dynamic C) on different hardware (standard PCs and embedded system controllers). An SR‐like run‐time system, DesCaRTeS, was developed to provide interprocess communication for the Dynamic C implementations. This paper compares load balancing and non‐load balancing implementations; it also compares CP and CM style implementations. The results show that in cases of very high or very low workloads, load balancing slightly hindered performance; and in cases of moderate workload, both SR and Dynamic C implementations of load balancing generally performed well. Further, for these applications, CM style programs outperform CP style programs in some cases, but the opposite occurs in some other cases. This paper also discusses qualitative tradeoffs between CM style programming and CP style programming for these applications. Copyright © 2004 John Wiley & Sons, Ltd.     

协作机制评价和全局联合最优搜索的通用模型

现有协作机制(CM)评价和选择模型存在通用性差、易陷入局部最优、CM库难以建立及评价函数设计困难等缺陷,不能满足现代复杂协同系统的要求。该文针对CM动态选择系统,构建CM评价的通用模型,设计对CM及其参数进行全局联合最优搜索的遗传算法,对模型和算法进行仿真。仿真结果表明,该模型能克服原有模型的缺陷,其算法能搜索到全局联合最优CM库。     

Two-stage approach for machine-part grouping and cell layout problems

Cellular manufacturing system (CMS) which is based on the concept of group technology (GT) has been recognized as an efficient and effective way to improve the productivity in a factory. In recent years, there have been continuous research efforts to study different facet of CMS. Most of them concentrated on distinguishing the part families and machine cells either simultaneously or individually with the objective of minimizing intercellular and intracellular part movements. This is known as machine-part grouping problem (MPGP) which is a crucial process while designing CMS. Nevertheless, in reality some components may not be finished within only one cell, they have to travel to another cell(s) for further operation(s). Under this circumstance, intercellular part movement will occur. Different order/sequence of machine cells allocation may result in different total intercellular movement distance unit. It should be noted that if the production volume of each part is very large, then the total number of intercellular movement will be further larger. Therefore, the sequence of machine cells is particularly important in this aspect. With this consideration, the main aim of this work is to propose two-stage approach for solving cell formation problem as well as cell layout problem. The first stage is to identify machine cells and part families, which is the essential part of MPGP. The work in second stage is to carry out a macro-approach to study the cell formation problem with consideration of machining sequence. The impact of the sequencing for allocating the machine cells on minimizing intercellular movement distance unit will be investigated in this stage. The problem scope, which is a MPGP together with the background of cell layout problem (CLP), has been identified. Two mathematical models are formulated for MPGP and CLP respectively. The primary assumption of CLP is that it is a linear layout. The CLP is considered as a quadratic assignment problem (QAP). As MPGP and QAP are NP-hard, genetic algorithm (GA) is employed as solving algorithm. GA is a popular heuristic search technique and has proved superior performance on complex optimization problem. In addition, an industrial case study of a steel member production company has been employed to evaluate the proposed MPGP and CLP models, and the computational results are presented.