Simulation-based optimization approach with scenario-based product sequence in a Reconfigurable Manufacturing System (RMS): A case study

In this study, we consider a production planning and resource allocation problem of a Reconfigurable Manufacturing System (RMS). Four general scenarios are considered for the product arrival sequence. The objective function aims to minimize total completion time of jobs. For a given set of input parameters defined by the market, we want to find the best configuration for the production line with respect to the number of resources and their allocation on workstations. In order to solve the problem, a hybridization approach based on simulation and optimization (Sim-Opt) is proposed. In the simulation phase, a Discrete Event Simulation (DES) model is developed. On the other hand, a simulated annealing (SA) algorithm is developed in Python to optimize the solution. In this approach, the results of the optimization feed the simulation model. On the other side, performance of these solutions are copied from simulation model to the optimization model. The best solution with the best performance can be achieved by this manually cyclic approach. The proposed approach is applied on a real case study from the automotive industry

Mass Production Processes

It is always hard to set manufacturing systems to produce large quantities of standardized parts. Controlling these mass production lines needs deep knowledge, hard experience, and the required related tools as well. The use of modern methods and techniques to produce a large quantity of products within productive manufacturing processes provides improvements in manufacturing costs and product quality. In order to serve these purposes, this book aims to reflect on the advanced manufacturing systems of different alloys in production with related components and automation technologies. Additionally, it focuses on mass production processes designed according to Industry 4.0 considering different kinds of quality and improvement works in mass production systems for high productive and sustainable manufacturing. This book may be interesting to researchers, industrial employees, or any other partners who work for better quality manufacturing at any stage of the mass production processes

A framework to offer high value manufacturing through self-reconfigurable manufacturing systems

The High Value Manufacturing (HVM) sector is vital for developed countries due to the creation of innovative products with advanced technology that cannot be reproduced at the same cost and time with traditional technology. The main challenge for HVM is to rapidly increase production volume from one-off products to low production volume. This requires highly flexible manufacturing systems that can produce new products at variable production volumes. Current manufacturing systems, classified as dedicated, flexible and reconfigurable systems, are limited to produce one type of product(s), within a production volume range and have fixed layouts of machines. Thus, there is a need for highly flexible systems that can rapidly adjust their production volume according to the production demand (i.e. main HVM challenge). Therefore, a novel manufacturing framework, called INTelligent REconfiguration for a raPID production change (INTREPID), is presented in this thesis. INTREPID consists of a user interface and communications platform, a job allocation system, a globally distributed network of Reconfigurable Manufacturing Centres (RMCs), consisting of interconnected factories, and Self-Reconfigurable Manufacturing Systems (S-RMSs). The highly flexible S-RMS consists of movable machines and Mobile Manufacturing Robots (MMRs). The novelty of the S-RMS is its capability of forming layouts bespoke to the current production needs. The vision of INTREPID is to offer global HVM services through the network of RMCs. The job allocation system determines the best possible RMCs or factories to perform a job by considering the complexity of the production requirements and the status of the available S-RMSs at each factory. The planning of the production with S-RMS is challenging due to its high flexibility. The main example of this flexibility is the possibility to create layouts bespoke to current production needs. Yet, this flexibility involves the challenges of determining allocations and schedules of tasks to robots and machines, positions to manufacture, and routes to reach those positions. In manufacturing systems with fixed layouts, production plans are determined by solving a sequence of problems. However, for the S-RMS, it is proposed to determine production plans with a single problem that covers the scheduling, machine layout and vehicle routing problems simultaneously. This novel problem is called the Scheduling, positions Assigning and Routing problem (SAR) problem. In order to determine the best possible production plan(s) for the S-RMS, it is necessary to use optimisation methods. Dozens of elements, characteristics and assumptions from the constituent problems might be included in the formulation of the SAR problem. Elements, characteristics and assumptions can be considered as decision variables on whether to include or not the elements and characteristics and under which assumptions in the formulation. There are two types of decision variables. Fundamental variables are natural to the SAR problem (e.g. manufacturing resources, factory design and operation), whilst auxiliary variables arise from the aim to simplify the formulation of the optimisation problem (i.e. time formulated as discrete or continuous). Due to the large number of decision variables, there might be millions of possible ways to formulate the SAR problem (i.e. the SAR problem space). Some of these variants are intractable to be solved with optimisation methods. Hence, before formulating the SAR problem, it is necessary to select a problem(s) that is realistic to industrial scenarios but solvable with optimisation methods. Existing selection methods work with pairwise comparisons of alternatives. However, for a space of millions of SAR problems, pairwise comparisons are intractable. Hence, in this thesis, a novel Decision Making Methodology (DMM) based on the controlled convergence method is presented. The DMM helps down-selecting one or a few SAR problems from millions of possible SAR problems. The DMM is demonstrated with a case study of the SAR problem and the results show a significant reduction of the reviewed SAR problems and the time to select them

Assembly line balancing and activity scheduling for customised products manufacturing

Nowadays, end customers require personalized products to match their specific needs. Thus, production systems must be extremely flexible. Companies typically exploit assembly lines to manufacture produces in great volumes. The development of assembly lines distinguished by mixed or multi models increases their flexibility concerning the number of product variants able to be manufactured. However, few scientific contributions deal with customizable products, i.e., produces which can be designed and ordered requiring or not a large set of available accessories. This manuscript proposes an original two-step procedure to deal with the multi-manned assembly lines for customized product manufacturing. The first step of the procedure groups the accessories together in clusters according to a specific similarity index. The accessories belonging to a cluster are typically requested together by customers and necessitate a significant mounting time. Thus, this procedure aims to split accessories belonging to the same cluster to different assembly operators avoiding their overloads. The second procedure step consists of an innovative optimization model which defines tasks and accessory assignment to operators. Furthermore, the developed model defines the activity time schedule in compliance with the task precedencies maximizing the operator workload balance. An industrial case study is adopted to test and validate the proposed procedure. The obtained results suggest superior balancing of such assembly lines, with an average worker utilization rate greater than 90%. Furthermore, in the worst case scenario in terms of customer accessories requirement, just 4 line operators out of 16 are distinguished by a maximum workload greater than the cycle time

Human system modelling in support of manufacturing enterprise design and change

Organisations comprise human and technical systems that typically perform a variety of business, engineering and production roles. Human systems comprise individuals, people groups and teams that work systematically to conceive, implement, develop and manage the purposes of any enterprise in response to customer requirements. Recently attention has been paid to modelling aspects of people working within production systems, with a view to improving: production performance, effective resource allocation and optimum resource management. In the research reported, graphical and computer executable models of people have been conceived and used in support of human systems engineering. The approach taken has been to systematically decompose and represent processes so that elemental production and management activities can be modelled as explicit descriptions of roles that human systems can occupy as role holders. First of all, a preliminary modelling method (MM1) was proposed for modelling human systems in support of engineering enterprise; then MM1 was implemented and tested in a case study company 1. Based on findings of this exploratory research study an improved modelling method (MM2) was conceived and instrumented. Here characterising customer related product dynamic impacts extended MM1 modelling concepts and methods and related work system changes. MM2 was then tested in case study company 2 to observe dynamic behaviours of selected system models derived from actual company knowledge and data. Case study 2 findings enabled MM2 to be further improved leading to MM3. MM3 improvements stem from the incorporation of so-called DPU (Dynamic Producer Unit) concepts, related to the modelling of human and technical resource system components . Case study 4 models a human system for targeted users i.e. production managers etc to facilitate analysis of human configuration and also cost modelling. Modelling approaches MM2, MM3 and also Case Study 4 add to knowledge about ways of facilitating quantitative analysis and comparison between different human system configurations. These new modelling methods allow resource system behaviours to be matched to specific, explicitly defined, process-oriented requirements drawn from manufacturing workplaces currently operating in general engineering, commercial furniture and white goods industry sectors

An integrated framework for developing generic modular reconfigurable platforms for micro manufacturing and its implementation

This thesis was submitted for the degree of Doctor of Philosophy and awarded by Brunel University.The continuing trends of miniaturisation, mass customisation, globalisation and wide use of the Internet have great impacts upon manufacturing in the 21st century. Micro manufacturing will play an increasingly important role in bridging the gap between the traditional precision manufacturing and the emerging technologies like MEMS/NEMS. The key requirements for micro manufacturing in this context are hybrid manufacturing capability, modularity, reconfigurability, adaptability and energy/resource efficiency. The existing design approaches tend to have narrow scope and are largely limited to individual manufacturing processes and applications. The above requirements demand a fundamentally new approach to the future applications of micro manufacturing so as to obtain producibility, predictability and productivity covering the full process chains and value chains. A novel generic modular reconfigurable platform (GMRP) is proposed in such a context. The proposed GMRP is able to offer hybrid manufacturing capabilities, modularity, reconfigurablity and adaptivity as both an individual machine tool and a micro manufacturing system, and provides a cost effective solution to high value micro manufacturing in an agile, responsive and mass customisation manner. An integrated framework has been developed to assist the design of GMRPs due to their complexity. The framework incorporates theoretical GMRP model, design support system and extension interfaces. The GMRP model covers various relevant micro manufacturing processes and machine tool elements. The design support system includes a user-friendly interface, a design engine for design process and design evaluation, together with scalable design knowledge base and database. The functionalities of the framework can also be extended through the design support system interface, the GMRP interface and the application interface, i.e. linking to external hardware and/or software modules. The design support system provides a number of tools for the analysis and evaluation of the design solutions. The kinematic simulation of machine tools can be performed using the Virtual Reality toolbox in Matlab. A module has also been developed for the multiscale modelling, simulation and results analysis in Matlab. A number of different cutting parameters can be studied and the machining performance can be subsequently evaluated using this module. The mathematical models for a non-traditional micro manufacturing process, micro EDM, have been developed with the simulation performed using FEA. Various design theories and methodologies have been studied, and the axiomatic design theory has been selected because of its great power and simplicity. It has been applied in the conceptual design of GMRP and its design support system. The implementation of the design support system is carried out using Matlab, Java and XML technologies. The proposed GMRP and framework have been evaluated through case studies and experimental results

Design and Management of Manufacturing Systems

Although the design and management of manufacturing systems have been explored in the literature for many years now, they still remain topical problems in the current scientific research. The changing market trends, globalization, the constant pressure to reduce production costs, and technical and technological progress make it necessary to search for new manufacturing methods and ways of organizing them, and to modify manufacturing system design paradigms. This book presents current research in different areas connected with the design and management of manufacturing systems and covers such subject areas as: methods supporting the design of manufacturing systems, methods of improving maintenance processes in companies, the design and improvement of manufacturing processes, the control of production processes in modern manufacturing systems production methods and techniques used in modern manufacturing systems and environmental aspects of production and their impact on the design and management of manufacturing systems. The wide range of research findings reported in this book confirms that the design of manufacturing systems is a complex problem and that the achievement of goals set for modern manufacturing systems requires interdisciplinary knowledge and the simultaneous design of the product, process and system, as well as the knowledge of modern manufacturing and organizational methods and techniques

Towards an integrated framework for the configuration of modular micro assembly systems

The future of manufacturing in high-cost economies is to maximise responsiveness to change whilst simultaneously minimising the financial implications. The concept of Reconfigurable Assembly Systems (RAS) has been proposed as a potential route to achieving this ideal. RASs offer the potential to rapidly change the configuration of a system in response to predicted or unforeseen events through standardised mechanical, electrical and software interfaces within a modular environment. This greatly reduces the design and integration effort for a single configuration, which, in combination with the concept of equipment leasing, enables the potential for reduction in system cost, reconfiguration cost, lead time and down time. This work was motivated by the slow implementation of the RAS concept in industry due, in part, to the limited research into the planning of multiple system reconfigurations. The challenge is to enable consideration of, and planning for, the production of numerous different products within a single modular, reconfigurable assembly environment. The developed methodology is to be structured and traceable, but also adaptable to specific and varying circumstances. This thesis presents an approach that aims towards providing a framework for the configuration of modular assembly systems. The approach consists of a capability model, a reconfiguration methodology and auxiliary functions. As a result, the approach facilitates the complete process of requirement elicitation, capability identification, definition and comparison, configuration analysis and optimisation and the generation of a system configuration lifecycle. The developed framework is demonstrated through a number of test case applications, which were used during the research, as well as the development of some specific technological applications needed to support the approach and application