GUI Toolbox for Approximation of Fractional Order Parameters With Application to Control of pH Neutralization Process

Fractional-order systems have been applied in many engineering applications. A key issue with the application of such systems is the approximation of fractional-order parameters. The numerical tools for the approximation of fractional-order parameters gained attention recently. However, available toolboxes in the literature do not have a direct option to approximate higher order systems and need improvements with the graphical, numerical, and stability analysis. Therefore, this chapter proposes a MATLAB-based GUI for the approximation of fractional-order operators. The toolbox is made up of four widely used approximation techniques, namely, Oustaloup, refined Oustaloup, Matsuda, and curve fitting. The toolbox also allows numerical and stability analysis for evaluating the performance of approximated transfer function. To demonstrate the effectiveness of the developed GUI, a simulation study is conducted on fractional-order PID control of pH neutralization process. The results show that the toolbox can be effectively used to approximate and analyze the fractional-order systems.

Study on Effect of Barriers in Green Supply Chain Management Using Modified SAW Technique

Nowadays along with the rapid development of industrialization across the globe, the environmental and ecological impacts of products have become a serious issue. Taking into account purely the economic impacts of industrial decisions, and excluding their ecological impacts, make the human beings and animals more at risk to many threats such as global warming, ozone layer depletion, toxic environments, and natural resources depletion. To minimize the environmental effect, implementation of green supply chain management (GSCM) is much more essential for industries in the environmental and social point of view. The purpose of this chapter is to analyze barriers to an implementation of green supply chain management in a stone crushing plant of Southern India by using modified simple additive weighting (SAW) to rank approaches. Further, this study will help the small-scale industries to understand the factors affecting implementation of GSCM in their organizations.

Multi-Objective Territory Design for Sales Managers of a Direct Sales Company

This chapter presents a case study to organize the sales territories for a company with 11 sales managers to be assigned to 111 sales coverage units in Mexico. The assignment problem is modeled as a mathematical program with two objective functions. One objective minimizes the maximum distance traveled by the manager, and the other objective minimizes the variation of the sales growth goals with respect to the national average. To solve the bi-objective non-linear mixed-integer program, a weights method is selected. Some instances are solved using commercial software with long computational times. Also, a heuristic and a metaheuristic based on simulated annealing were developed. The design of the heuristic generates good solutions for the distance objective. The metaheuristic produces better results than the heuristic, with a better balance between the objectives. The heuristic and the metaheuristic are capable of providing good results with short computational times.

Improvement Proposal in Inventories at an Automotive Supply Company Settled in Mexico

Controlling inventories and achieving effective management of them can significantly improve the profits to any company. This chapter presents a case of study of an automotive supply company that has operational problems due to over inventories. An ABC study and the economic order quantity model (EOQ) for 942 raw materials are presented promptly in order to increase the rotation efficiently, the yield of their inventories, as well as to minimize the logistics costs and maximize medium and long-term operations.

Semantic Web Service for Global Apparel Business

Nowadays a substantial share of the production processes of the world's apparel business is taking place in developing countries. In the apparel business, supply chain coordination needs resource and information sharing between business partners. Semantic web service computing (SWSC) provides numerous opportunities and value-added service capabilities that global apparel business requires to exchange information between distributed business partners. The ability to dynamically discover and invoke a web service is an important aspect of semantic web service-based architectures. This chapter describes the main features of an ontology-based web service framework, known as CSIA (collaborative service integration architecture) for integrating distributed business information systems in a global supply chain. The CSIA framework uses a hybrid knowledge-based system, which consists of structural case-based reasoning (S-CBR), rule-based reasoning (RBR), and an ontology concept similarity assessment algorithm.

Role of R&D Practices for Effective Product Development Process in NPD

The necessity of new product development (NPD) in the global competition is a well-established fact. Imperativeness of research and development (R&D) practices and product development process (PDP) in NPD are inevitable. In case of R&D practices, fuzzy-front-end (FFE) activities and improvisation are the two sub-factors which are not directly related to R&D but motivate it indirectly with their actions. For PDP, modular product development (MPD) and market analysis are recognized as the factors directly influencing the PDP of the firm for NPD success. This chapter considers product quality and technological developments as performance attributes for development of comprehensive framework by structural equation modeling (SEM) approach. Primary data from 263 experts of Indian manufacturing industries has been collected for analysis purpose. This empirical research portrays the role of R&D practices along with its indirectly related success factors for effectively controlling PDP along with its sub-factors for developing high quality products with technological developments.

Linear Programming Based on Piece-Wise Linearization for Solving the Economic Load Dispatch Problem

This chapter discusses the application of linear programming (LP) techniques to find the optimal solution of the economic dispatch (ED) problem without considering transmission losses. The ED problem is concerned with optimizing the power generated by several generating units. The objective is to find the optimal power produced by each unit to supply the required load at minimum total cost. The generation cost associated with each unit is usually in the form of a quadratic or cubic function of the power produced. To apply LP, these nonlinear cost functions have to be linearized. The optimal solution is then determined by LP based on the approximate linear model. Piece-wise linearization methodology is adopted in this chapter. To evaluate the performance of the linearization method, a comprehensive set of benchmark test problems is used. LP solutions of linearized ED problems are compared with several other techniques from the literature. The LP technique with piece-wise linearization shows an overall competitive advantage in terms of total cost, solution time, and load satisfaction.

Bio-Inspired Meta-Heuristic Multi-Objective Optimization of EDM Process

Modern-day engineering is trending toward complex devices with high accuracy and precision while at the same time the workpiece materials are becoming harder and more complex alloys. Non-conventional machining helps to sustain industries in this challenging environment. Electric discharge machining is one such precision machining that can produce complex product with great accuracy. This machine can be utilized in the manufacturing of complicated shaped die for plastic molding, automobile parts, aerospace, and other applications. In solving real-world problems like engineering design, business planning, and network design, challenges are being faced due to highly non-linear data and limited resources like time and money. Optimization is the best choice to solve such practical problems efficiently. This chapter deals with the optimization of EDM process parameters using two different bio-inspired optimization algorithms, namely, artificial bee colony algorithm and whale optimization algorithm, for both single as well as multiple responses and compares the results.

Lean Six Sigma Implementation Framework Using Resource-Based Theory Approach

Resource-based theory (RBT) is one of the most popular paradigms in operations management. Lean Six Sigma (LSS) is the most widely used business improvement initiative for the last two decades. The previous LSS frameworks were concentrated on the LSS processes, and none of them proposed a link between organizational strategy, organizational resources and capabilities for gaining competitive advantage. The purpose of this chapter is to construct an RBT-based LSS framework. By reviewing the previous literature on RBT, LSS and organizational strategy, this chapter builds an implementation framework. This framework considers the firm resources, firm capability, competitive advantage, and LSS integration as the foundation of a firm's strategy. The research suggests that application of RBT can add richness to LSS implementation within an organization, which will bring practical implications for forming the resource-based strategy in the organizations leading to competitive advantage. This is the first chapter to suggest an integration framework of RBT with LSS for strategy implications.

A MILP and Genetic Algorithm Approach for a Furniture Manufacturing Flow Shop Scheduling Problem

A MILP and genetic algorithm optimization model for the sequencing of jobs in a medium-sized factory, dedicated to the manufacturing of home furniture, where different categories and types of articles are produced and whose routes and manufacturing processing times vary widely, are proposed. Different scenarios are considered for the objective function based on minimizing makespan and tardiness. The results of the optimization for an instance of 24 jobs on five machines, chosen as a representative instance of the order sizes that are handled by the company, show important reductions in the productive system's usage times, oscillating between 10% and 20% with respect to a random initial sequence in the production plan. Improvements were similar in both techniques, the main difference being the solution time of each one.