The relevance of outsourcing and leagile strategies in performance optimization of an integrated process planning and scheduling

Over the past few years growing global competition has forced the manufacturing industries to upgrade their old production strategies with the modern day approaches. As a result, recent interest has been developed towards finding an appropriate policy that could enable them to compete with others, and facilitate them to emerge as a market winner. Keeping in mind the abovementioned facts, in this paper the authors have proposed an integrated process planning and scheduling model inheriting the salient features of outsourcing, and leagile principles to compete in the existing market scenario. The paper also proposes a model based on leagile principles, where the integrated planning management has been practiced. In the present work a scheduling problem has been considered and overall minimization of makespan has been aimed. The paper shows the relevance of both the strategies in performance enhancement of the industries, in terms of their reduced makespan. The authors have also proposed a new hybrid Enhanced Swift Converging Simulated Annealing (ESCSA) algorithm, to solve the complex real-time scheduling problems. The proposed algorithm inherits the prominent features of the Genetic Algorithm (GA), Simulated Annealing (SA), and the Fuzzy Logic Controller (FLC). The ESCSA algorithm reduces the makespan significantly in less computational time and number of iterations. The efficacy of the proposed algorithm has been shown by comparing the results with GA, SA, Tabu, and hybrid Tabu-SA optimization methods

Chapter 13 - Sharing strategies: carsharing, shared micromobility (bikesharing and scooter sharing), transportation network companies, microtransit, and other innovative mobility modes

Shared mobility—the shared use of a vehicle, bicycle, or other mode—is an innovative transportation strategy that enables users to gain short-term access to transportation modes on an “as-needed” basis. It includes various forms of carsharing, bikesharing, scooter sharing, ridesharing (carpooling and vanpooling), transportation network companies (TNCs), and microtransit. Included in this ecosystem are smartphone “apps” that aggregate and optimize these mobility options, as well as “courier network services” that provide last mile package and food delivery. This chapter describes different models that have emerged in shared mobility and reviews research that has quantified the environmental, social, and transportation-related impacts of these services

Energy efficiency in discrete-manufacturing systems: insights, trends, and control strategies

Since the depletion of fossil energy sources, rising energy prices, and governmental regulation restrictions, the current manufacturing industry is shifting towards more efficient and sustainable systems. This transformation has promoted the identification of energy saving opportunities and the development of new technologies and strategies oriented to improve the energy efficiency of such systems. This paper outlines and discusses most of the research reported during the last decade regarding energy efficiency in manufacturing systems, the current technologies and strategies to improve that efficiency, identifying and remarking those related to the design of management/control strategies. Based on this fact, this paper aims to provide a review of strategies for reducing energy consumption and optimizing the use of resources within a plant into the context of discrete manufacturing. The review performed concerning the current context of manufacturing systems, control systems implemented, and their transformation towards Industry 4.0 might be useful in both the academic and industrial dimension to identify trends and critical points and suggest further research lines.Peer ReviewedPreprin

A modular hybrid simulation framework for complex manufacturing system design

For complex manufacturing systems, the current hybrid Agent-Based Modelling and Discrete Event Simulation (ABM–DES) frameworks are limited to component and system levels of representation and present a degree of static complexity to study optimal resource planning. To address these limitations, a modular hybrid simulation framework for complex manufacturing system design is presented. A manufacturing system with highly regulated and manual handling processes, composed of multiple repeating modules, is considered. In this framework, the concept of modular hybrid ABM–DES technique is introduced to demonstrate a novel simulation method using a dynamic system of parallel multi-agent discrete events. In this context, to create a modular model, the stochastic finite dynamical system is extended to allow the description of discrete event states inside the agent for manufacturing repeating modules (meso level). Moreover, dynamic complexity regarding uncertain processing time and resources is considered. This framework guides the user step-by-step through the system design and modular hybrid model. A real case study in the cell and gene therapy industry is conducted to test the validity of the framework. The simulation results are compared against the data from the studied case; excellent agreement with 1.038% error margin is found in terms of the company performance. The optimal resource planning and the uncertainty of the processing time for manufacturing phases (exo level), in the presence of dynamic complexity is calculated

A Novel Hybrid Framework for Co-Optimization of Power and Natural Gas Networks Integrated With Emerging Technologies

In a power system with high penetration of renewable power sources, gas-fired units can be considered as a back-up option to improve the balance between generation and consumption in short-term scheduling. Therefore, closer coordination between power and natural gas systems is anticipated. This article presents a novel hybrid information gap decision theory (IGDT)-stochastic cooptimization problem for integrating electricity and natural gas networks to minimize total operation cost with the penetration of wind energy. The proposed model considers not only the uncertainties regarding electrical load demand and wind power output, but also the uncertainties of gas load demands for the residential consumers. The uncertainties of electric load and wind power are handled through a scenario-based approach, and residential gas load uncertainty is handled via IGDT approach with no need for the probability density function. The introduced hybrid model enables the system operator to consider the advantages of both approaches simultaneously. The impact of gas load uncertainty associated with the residential consumers is more significant on the power dispatch of gas-fired plants and power system operation cost since residential gas load demands are prior than gas load demands of gas-fired units. The proposed framework is a bilevel problem that can be reduced to a one-level problem. Also, it can be solved by the implementation of a simple concept without the need for Karush–Kuhn–Tucker conditions. Moreover, emerging flexible energy sources such as the power to gas technology and demand response program are considered in the proposed model for increasing the wind power dispatch, decreasing the total operation cost of the integrated network as well as reducing the effect of system uncertainties on the total operating cost. Numerical results indicate the applicability and effectiveness of the proposed model under different working conditions

The impact of enterprise application integration on information system lifecycles

Information systems (IS) have become the organisational fabric for intra-and inter-organisational collaboration in business. As a result, there is mounting pressure from customers and suppliers for a direct move away from disparate systems operating in parallel towards a more common shared architecture. In part, this has been achieved through the emergence of new technology that is being packaged into a portfolio of technologies known as enterprise application integration (EAI). Its emergence however, is presenting investment decision-makers charged with the evaluation of IS with an interesting challenge. The integration of IS in-line with the needs of the business is extending their identity and lifecycle, making it difficult to evaluate the full impact of the system as it has no definitive start and/or end. Indeed, the argument presented in this paper is that traditional life cycle models are changing as a result of technologies that support their integration with other systems. In this paper, the need for a better understanding of EAI and its impact on IS lifecycles are discussed and a classification framework proposed.Engineering and Physical Sciences Research Council (EPSRC) Grant Ref: (GR/R08025) and Australian Research Council (DP0344682)