KEYWORDS: Signal processing, Signal detection, Process control, Wavelet transforms, Wavelets, Manufacturing, Pattern recognition, Sensors, Data storage, Data modeling
Manufacturing processes are generally monitored by observing uniformly sampled process signals collected from
application specific sensors. Effective process monitoring and control requires identification of different types of
variations, including recurring patterns, in process variables. From the process control view point, any repeating patterns
in the process measurements will warrant an investigation into potentially assignable causes. In order to devise an
effective process control scheme, a novel method for identifying the repeated occurrence of patterns in process
measurements is described in this paper. First the sampled process signal is decomposed into signals of different
resolution using a wavelet transform. Next, a frequency index is assigned to every sampling point of the process signal at
every resolution level to improve the pattern recognition. Recurring patterns are first detected at different resolutions and
are then integrated to arrive at the final results. The experimental results show that the method used in this work
accurately detects a broader family of recurring patterns even in the presence of noise.
Independent and small scale product recovery facilities (PRFs) often struggle to achieve profits when faced with inconsistent inflows of discarded products, varying demand patterns for recovered components, and stringent environmental regulations. Inconsistent inflows coupled with the varying demand cause undue fluctuations in inventory levels and frequently affect costs involved in product recovery operations. An effective pricing strategy can stabilize the fluctuations in demand and consequently can allow PRFs to control inventory levels. This research determines the prices of reusable and recyclable components and acquisition price of discarded products that allow PRFs to simultaneously maximize their financial returns and minimize the product recovery costs. Genetic algorithms and analytic hierarchy process are employed to solve this multi-criteria decision making problem.
Discrete wavelet transform has become a widely used feature extraction tool in pattern recognition and pattern classification applications. However, using all wavelet coefficients as features is not desirable in most applications -- the enormity of data and irrelevant wavelet coefficients may adversely affect the performance. Therefore, this paper presents a novel feature extraction method based on discrete wavelet transform. In this method, Shannon's entropy measure is used for identifying competent wavelet coefficients. The features are formed by calculating the energy of coefficients clustered around the competent clusters. The method is applied to the lung sound classification problem. The experimental results show that the new method performs better than a well-known feature extraction method that is known to give the best results for lung sound classification problem.
The main objective of a product recovery facility (PRF) is to disassemble end-of-life (EOL) products and sell the reclaimed components for reuse and recovered materials in second-hand markets. Variability in the inflow of EOL products and fluctuation in demand for reusable components contribute to the volatility in inventory levels. To stay profitable the PRFs ought to manage their inventory by regulating the price appropriately to minimize holding costs. This work presents two deterministic pricing models for a PRF bounded by environmental regulations. In the first model, the demand is price dependent and in the second, the demand is both price and time dependent. The models are valid for single component with no inventory replenishment sale during the selling horizon . Numerical examples are presented to illustrate the models.
This research investigates the advantages offered by embedded sensors for cost-effective and environmentally benign product life cycle management for desktop computers. During their use by customers as well as at the end of their lives, Sensor Embedded Computers (SECs) by virtue of sensors embedded in them generate data and information pertaining to the conditions and remaining lives of important components such as hard-drive, motherboard, and power supply unit. A computer monitoring framework is proposed to provide more customer comfort, reduce repair costs and increase the effectiveness of current disassembly practices. The framework consists of SECs, remote monitoring center (RMC), repair/service, disassembly, and disposal centers. The RMC collects dynamic data/information generated by sensors during computer usage as well as static data/information from the original equipment manufacturers (OEMs). The RMC forwards this data/information to the repair/service, disassembly, and disposal centers on need-basis. The knowledge about the condition and remaining life of computer components can be advantageously used for planning repair/service and disassembly operations as well as for building refurbished computers with known expected lives. Simulation model of the framework is built and is evaluated in terms of the following performance measures: average downtime of a computer, average repair/service cost of a computer, average disassembly cost of a computer, and average life cycle cost of a computer. Test results show that embedding sensors in computers provides a definite advantage over conventional computers in terms of the performance measures.
Packaging material selection (PMS) problems have always been important to packaging designers and engineers. Not only does the selection of packaging material determine the costs and the environmental impacts of packaging, but also influences packaging physical characteristics and associated manufacturing methods. In order to reduce economic and environmental impacts, one has to take a holistic approach to packaging material selection by considering material effects throughout the packaging life cycle. To evaluate economic costs and environmental impacts both quantitative factors and subjective criteria play an important role in the packaging design. In the present work, fuzzy set theory is used for representing and manipulating the vague and subjective descriptions of packaging performance and design attributes. Further a genetic algorithm based approach is used for addressing the packaging material selection problem through multiple criteria decision-making. The overall approach comprises of two phases. In the first phase, fuzzy set theory is used for the linguistic transformation of performance attributes into numerical values. It results in a decision matrix that contains crisp scores. Also in this phase, a weight is assigned to each sub-criterion to show its importance compared to others. In the second phase, a GA is used to globally search for near-optimal or optimal design solutions. The implementation of the proposed methodology is illustrated through a numerical example.
The driving forces behind product take-back and green manufacturing are well established. The two main product end-of-life options are reuse/remanufacturing and recycling. For either option, all take-back units are treated equally because no information that tracks the conditions of a product during its useful life is available. For example, all expired PCs are treated equally; no distinction can be made about which units still have healthy hard disks. This paper discusses sensor-based monitoring and prognostic methodologies for tracking the condition of products while being used by customers and timely and targeted servicing, smart and selective disassembling and refurbishing of products with known (long) remaining lives. The paper also discusses the added benefits to product manufacturers when the time comes to redesign their products. The real-time field data on service and utilization of products are communicated to manufacturers’ headquarters for further analysis.
It is difficult to obtain information regarding compositions and remaining life periods of used products. Hence, they often undergo partial or complete disassembly for subsequent re-processing (remanufacturing and/or recycling). However, researchers are now studying sensor embedded products (SEPs), the composition and remaining life of which can be obtained at the end of their use from sensors. This paper addresses decision-making regarding the futurity of an SEP at its end of use: whether to disassemble it for subsequent recycling/remanufacturing or to repair it for subsequent sale on a second-hand market. We identify some important factors that must be considered before making a decision. Using a numerical example, we propose a simple approach that employs Bayesian updating and fuzzy set theory to aid the decision-making process.
The use of personal computers (PCs) continues to increase every year. According to a 1999 figure, 50 percent of all US households owned PCs, a figure that continues to rise every year. With continuous development of sophisticated software, PCs are becoming increasingly powerful. In addition, the price of a PC continues to steadily decline. Furthermore, the typical life of a PC in the workplace is approximately two to three years while in the home it is three to five years. As these PCs become obsolete, they are replaced and the old PCs are disposed of. It is estimated that between 14 and 20 million PCs are retired annually in the US. While 20 to 30% of the units may be resold, the others are discarded. These discards represent a significant potential source of lead for the waste stream. In some communities, waste cathode ray tubes (CRTs) represent the second largest source of lead in the waste stream after vehicular lead acid batteries. PCs are, therefore, not suitable for dumping in landfills. Besides, several components of a PC can be reused and then there are other valuable materials that can also be harvested. And with the advent of product stewardship, product recovery is the best solution for manufacturers. Disassembly line is perhaps the most suitable set up for disassembling PCs. However, planning and scheduling of disassembly on a disassembly line is complicated. In this paper, we discuss some of the complications including product arrival, demand arrival, inventory fluctuation and production control mechanisms. We then show how to overcome them by implementing a multi-kanban mechanism in the PC disassembly line setting. The multi-kanban mechanism relies on dynamic routing of kanbans according to the state of the system. We investigate the multi-kanban mechanism using simulation and demonstrate that this mechanism is superior to the traditional push system in terms of controlling the system’s inventory while maintaining a decent customer service level.
Taking a multi-resolution approach, this research work proposes an effective algorithm for aligning a pair of scans obtained by scanning an object's surface from two adjacent views. This algorithm first encases each scan in the pair with an array of cubes of equal and fixed size. For each scan in the pair a surrogate scan is created by the centroids of the cubes that encase the scan. The Gaussian curvatures of points across the surrogate scan pair are compared to find the surrogate corresponding points. If the difference between the Gaussian curvatures of any two points on the surrogate scan pair is less than a predetermined threshold, then those two points are accepted as a pair of surrogate corresponding points. The rotation and translation values between the surrogate scan pair are determined by using a set of surrogate corresponding points. Using the same rotation and translation values the original scan pairs are aligned. The resulting registration (or alignment) error is computed to check the accuracy of the scan alignment. When the registration error becomes acceptably small, the algorithm is terminated. Otherwise the above process is continued with cubes of smaller and smaller sizes until the algorithm is terminated. However at each finer resolution the search space for finding the surrogate corresponding points is restricted to the regions in the neighborhood of the surrogate points that were at found at the preceding coarser level. The surrogate corresponding points, as the resolution becomes finer and finer, converge to the true corresponding points on the original scans. This approach offers three main benefits: it improves the chances of finding the true corresponding points on the scans, minimize the adverse effects of noise in the scans, and reduce the computational load for finding the corresponding points.
KEYWORDS: Packaging, Picosecond phenomena, Manufacturing, Inspection, Virtual colonoscopy, Compact discs, Systems modeling, Cadmium, Voltage controlled voltage source, Time metrology
Returnable transport packaging plays an important role in facilitating the transfer of a large volume of products in a close-loop distribution network. To make effective use of returnable transport packaging, vehicle dispatching strategies are crucial. With an appropriate vehicle dispatching strategy, for example, a fast turnover time and a short waiting time for packaging dispatch can be achieved. However, there are some factors that directly influence vehicle dispatching strategies. These factors include the arrival demand fluctuations, the availability of serving vehicles, and the geographic proximity of the facility to the customer’s locations. In this study, authors investigate the effect of these factors on vehicle dispatching strategies for transport packaging by using a simulation modeling approach. This paper reports different performance outcomes obtained through various test cases.
Smart sensors and their networking technology when applied in manufacturing environment for monitoring, diagnostics, and control and for data/information collection could dwarf all the advances made so far by the manufacturing community through traditional sensors. Smart sensors can significantly contribute to improving automation and reliability through high sensitivity, self-calibration and compensation of non-linearity, low-power operation, digital pre-processed output, self-checking and diagnostic modes, and compatibility with computers and other subsystem blocks. There is a huge gulf between the existing models of manufacturing systems and the computational models that are required to correctly characterize manufacturing systems integrated with smart sensor networks. This paper proposes a multi-agent model for S2IM system. The agent characteristics and the expected model behavior are presented.
It has become common for manufacturing facilities involved in production of new products to also carry out collection and re-processing of used products. While environmental consciousness has become an obligation to the facilities in the production of new products due to governmental regulations and public perspective on environmental issues, potentiality of the facilities to re-process used products directly affects the profitability of the facilities. Although many papers in the literature deal with performance evaluation of facilities, none of them address these two factors. To this end, a TOPSIS (Technique for Order Preference by Similarity to an Ideal Solution) approach, which evaluates production facilities in
terms of both environmental-consciousness and potentiality, is proposed. Furthermore, since most of the criteria that fall
under these two factors are intangible, triangular fuzzy numbers (TFNs) are employed to rate them in the evaluation process. A numerical example demonstrates the feasibility of the proposed method.
Although there are many quantitative models in the literature to design a reverse supply chain, every model assumes that all the recovery facilities that are engaged in the supply chain have enough potential to efficiently re-process the incoming used products. Motivated by the risk of re-processing used products in facilities of insufficient potentiality, this paper proposes a method to identify potential facilities in a set of candidate recovery facilities operating in a region where a reverse supply chain is to be established. In this paper, the problem is solved using a newly developed method called physical programming. The most significant advantage of using physical programming is that it allows a decision
maker to express his preferences for values of criteria (for comparing the alternatives), not in the traditional form of weights but in terms of ranges of different degrees of desirability, such as ideal range, desirable range, highly desirable range, undesirable range, and unacceptable range. A numerical example is considered to illustrate the proposed method.
The main thrust of returnable packaging these days is to provide logistical services through transportation and distribution of products and be environmentally friendly. Returnable packaging and reverse logistics concepts have converged to mitigate the adverse effect of packaging materials entering the solid waste stream. Returnable packaging must be designed by considering the trade-offs between costs and environmental impact to satisfy manufacturers and
environmentalists alike. The cost of returnable packaging entails such items as materials, manufacturing, collection, storage and disposal. Environmental impacts are explicitly linked with solid waste, air pollution, and water pollution. This paper presents a multi-criteria evaluation technique to assist decision-makers for evaluating the trade-offs in costs and environmental impact during the returnable packaging design process. The proposed evaluation technique involves a combination of multiple objective integer linear programming and analytic hierarchy process. A numerical example is
used to illustrate the methodology.
This paper presents a framework for a collaboration platform that facilitates agile design process. The paper specifies the drivers for building such a collaboration platform, identifies its attributes, and proposes the mechanisms for resolving its dilemmas. The primary force that is driving agile product design is the market demand for the 'right products,' which have three attributes: (1) right features, (2) right time to market, and (3) right cost. The success of a company in marketplace is decided by how well it strikes a balance between these three attributes while developing new products. There have been several productivity boosting techniques such as CAD, CAM, CAE tools to assist designers at each stage of product development. However, the total product development process has not benefitted much from them, because of the inherent delays between the stages that account for 30 to 90 percent of the total product development time. An innovative approach, which employs web- based collaboration tools, can offer dramatic improvements in the process of introducing 'right products' into the market. The paper contends that an ideal collaboration platform should enable any designer located anywhere to design products using any CAD and any PDM on any platform. Such a collaboration platform potentially (1) reduces product development time, (2) curtails product development cost, and (3) improves the chances for first to market.
This paper presents a new technique which uses a tree for constraining the compatibility among components in a logical bill of material (BOM) structure. The new representation for restricting possible combinations of components is designed to address the limitations of matrix representations that were used for the same purpose in earlier work. These matrix representations, which assume that the compatibility in a BOM can always be described for pairs of components, cannot be used for products in which the compatibility among three or more components is an issue. Thus, it is proposed to use a standard tree with a special representation, which is called a trie, to represent the compatibility between the components in a product configuration. Similar to the inter-component compatibility matrix, the trie can be used to validate and/or complete an arbitrary product configuration during the configuration process without having to spell out product configuration rules. The new representation provides the user with a means to describe all possible compatibility relationships with a limited amount of data. This trie representation is comprehensive, easy to maintain, and easy to understand.
Disassembly line is, perhaps, the most suitable way for the disassembly of large products or small products in large quantities. In this paper, we address the disassembly line balancing problem (DLBP) and the challenges that come with it. The objective ofbalancing the disassembly line is to utilize the disassembly line in an optimized fashion while meeting the demand for the parts retrieved from the returned products. Although, the traditional line balancing problem for assembly has been studied for a long time, so far, no one has formally talked about the DLBP. In this work, our primary objective is to address the DLBP related issues. However, we also present a heuristic to demonstrate how several important factors in disassembly can be incorporated into the solution process of a DLBP. An example is considered to illustrate the use of the heuristic.
Today's competitive enterprises need to design, develop, and manufacture their products rapidly and inexpensively. Agile manufacturing has emerged as a new paradigm to meet these challenges. Agility requires, among many other things, scheduling and control software systems that are flexible, robust, and adaptive. In this paper a new agent-based scheduling system (ABBS) is developed to meet the challenges of an agile manufacturing system. In ABSS, unlike in the traditional approaches, information and decision making capabilities are distributed among the system entities called agents. In contrast with the most agent-based scheduling systems which commonly use a bidding approach, the ABBS employs a global performance monitoring strategy. A production-rate-based global performance metric which effectively assesses the system performance is developed to assist the agents' decision making process. To test the architecture, an agent-based discrete event simulation software is developed. The experiments performed using the simulation software yielded encouraging results in supporting the applicability of agent-based systems to address the scheduling and control needs of an agile manufacturing system.
In recent times, while markets are reaching their saturation limits and customers are becoming more demanding, a paradigm shift has been taking place from mass production to mass- customized production (MCP). The concept of mass customization (MC) focuses on satisfying a customer's unique needs with the help of new technologies such as Internet, digital product realization, and re-configurable production facilities. In MC the needs of an individual customer are translated into design, accordingly produced, and delivered to the customer. In this research three hypothesis related to MCP are investigated by the data/information collected from ten companies, which are engaged in MCP. These three hypothesis are (1) mass-customized production systems can be classified into make-to-stock MCP, assemble-to-order MCP, make-to-order MCP, engineer-to-order MC, and develop-to-order MCP, (2) in mass-customized production systems the process of customization eliminates customer sacrifice, and (3) mass-customized production systems can deliver products at mass-production cost. The preliminary study indicates that while the first hypothesis is valid, MCP companies rarely fulfill what is stated in the other two hypotheses.
For make-to-order products in which the specification of some component-product variants are to be defined by customers, it is almost impossible to develop a bill-of-material system that supports customers' requests for quotation (RFQ) response activities using the existing bill-of-material concepts. To deal with this problem, a new technique for representing the relationship between parent-product variants and componenent- product variants in the generic bill-of-material (GBOM) structure is developed. The new technique is based on an assumption that the relationship between any two components in a product structure has pairwise independent property. The technique represents the relationship with compatibility constraints in the form of matrices and rules. The new representation provides users with a means to describing variants of make-to-order products as well as supporting the customers' RFQ response activities with only a limited amount of data which is comprehensive, easy to maintain, and easy to understand.
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