Assessment of usage of planning & scheduling procedures & ICT by UK manufacturing SME's

Dissertação de mestrado em Engineering and Management of Manufacturing SystemsThis dissertation investigates the practices of scheduling and data management in small and medium manufacturing enterprises (SMEs). This work intends to identify and assess the stage of usage of tools and/or software used in companies across the UK, and their techniques. To make this assessment and compare the results within these practices, a combination of a webquestionnaire and interviews were carried out, where participants are asked for their insight and evaluation on issues that were found in literature. To better analyse the impact of the tools and techniques, results were compared within these practices, the companies that show better results or lack of success are analysed by a series of performance indicators that may identify the result of such tools and techniques. To perform this survey, a literature review was carried out to discover previous research that has been conducted on the topic and identify the gaps between theory and practices. Research presents positive and negative aspects of the more common and traditional scheduling tools, a classification for manufacturing scheduling tools, and the usage of ERP systems in SMEs. Data was collected from the companies and is than analysed and discussed to identify trends and produce conclusions on the practices of UK manufacturing companies

Human aspects of scheduling : a case study

Thesis (S.M.)--Massachusetts Institute of Technology, Engineering Systems Division, September 2006.Includes bibliographical references (leaves 64-68).This work presents a look at real-life production-floor scheduling, comparing and contrasting it to both normative OR theory and Cognitive Psychology theory. Relevant literature in OR, scheduling and psychology is reviewed, and gaps in theory are pointed out, calling for observation of real-life scheduling and for modeling of the cognitive processes underlying such activities. While normative theory and cognitive psychology theory suggest certain behaviors should be observed, a case study conducted with a large manufacturing company reveals real-life scheduling to be different from behavior expected by OR as well as by cognitive psychology. Future research is suggested, which may enable better modeling of human schedulers.by Yishai Boasson.S.M

Integrated decision support for planning, scheduling, and dispatching tasks in a focused factory

Standard software for decision support in production control tasks is commonly structured according to the hierarchical production planning (HPP) concept. However, in a focused factory one planner may carry out planning, scheduling and dispatching. This paper presents a case study where one integrated planner is responsible for planning, scheduling and dispatching. Hence, the integrated planner needs a seamless system from the generation from the daily level through the generation of the 5-year-plan. This paper presents a design of a decision support system for the integrated planner

A knowledge sharing framework to support rapid prototyping in collaborative automotive supply chain

In today’s global economy, competition is increasingly driven by a high rate of product renewal. In this context, with market demands for the development of high quality products at lower costs, highly customisable and with short life cycles, new technologies have been adopted by the automotive manufacturers in the move away from a local economy towards the global economy. The continuous evolution of this technology often requires the updating and integration of existing systems within new environments, in order to avoid technological obsolescence. To allow companies to compete in the global market, they (the companies) can no longer be seen acting as standalone entities and are having to reconsider their organisational and operational structure. This thesis presents a Knowledge Sharing Framework Design Roadmap to support rapid prototyping in the automotive and collaborative supply chain. IranKhodro Diesel (IKD) is the automotive company and CarGlass Company (Iran) is the supplier and sponsor of this research study. These two companies will be used to develop and test the Knowledge Sharing Framework Design Roadmap (KSFDR) methodology. An industrially based case study was conducted in IKD and CarGlass to identify key elements in the Knowledge Sharing Framework and provide the focus for this study. The study itself drew on empirical sources of data, including interviews with IKD personnel via an internal company survey. The absence of mechanisms to make information accessible in a multilingual environment and its dissemination to geographically dispersed NPD project team members was identified along with the lack of explicit information about the knowledge used and generated to support first stage rapid prototyping in the product development process with respect to reduction of costs and lead times. The Knowledge Sharing Framework Design Roadmap was tested between IKD and CarGlass. The business objectives in both IKD and CarGlass are the main drivers of knowledge system development. The main novel point from this research study is that this particular framework can be used to capture and disseminate information and knowledge. This was supported by positive feedback from a series of interviews with NPD practitioners. The Knowledge Sharing Framework Design Roadmap (KSFDR) methodology, however, can also be applied in other manufacturing and business environments. Further testing of the framework is strongly advised to minimise any minor flaws, which remain

A real-time simulation-based optimisation environment for industrial scheduling

n order to cope with the challenges in industry today, such as changes in product diversity and production volume, manufacturing companies are forced to react more flexibly and swiftly. Furthermore, in order for them to survive in an ever-changing market, they also need to be highly competitive by achieving near optimal efficiency in their operations. Production scheduling is vital to the success of manufacturing systems in industry today, because the near optimal allocation of resources is essential in remaining highly competitive. The overall aim of this study is the advancement of research in manufacturing scheduling through the exploration of more effective approaches to address complex, real-world manufacturing flow shop problems. The methodology used in the thesis is in essence a combination of systems engineering, algorithmic design and empirical experiments using real-world scenarios and data. Particularly, it proposes a new, web services-based, industrial scheduling system framework, called OPTIMISE Scheduling System (OSS), for solving real-world complex scheduling problems. OSS, as implemented on top of a generic web services-based simulation-based optimisation (SBO) platform called OPTIMISE, can support near optimal and real-time production scheduling in a distributed and parallel computing environment. Discrete-event simulation (DES) is used to represent and flexibly cope with complex scheduling problems without making unrealistic assumptions which are the major limitations of existing scheduling methods proposed in the literature. At the same time, the research has gone beyond existing studies of simulation-based scheduling applications, because the OSS has been implemented in a real-world industrial environment at an automotive manufacturer, so that qualitative evaluations and quantitative comparisons of scheduling methods and algorithms can be made with the same framework. Furthermore, in order to be able to adapt to and handle many different types of real-world scheduling problems, a new hybrid meta-heuristic scheduling algorithm that combines priority dispatching rules and genetic encoding is proposed. This combination is demonstrated to be able to handle a wider range of problems or a current scheduling problem that may change over time, due to the flexibility requirements in the real-world. The novel hybrid genetic representation has been demonstrated effective through the evaluation in the real-world scheduling problem using real-world data