Dynamic lot sizing and tool management in automated manufacturing systems

Cataloged from PDF version of article.The overall aim of this study is to show that there is a critical interface between the lot sizing and tool management decisions, and these two problems cannot be viewed in isolation. We propose "ve alternative algorithms to solve lot sizing, tool allocation and machining conditions optimization problems simultaneously. The "rst algorithm is an exact algorithm which "nds the global optimum solution, and the others are heuristics equipped with a look-ahead mechanism to guarantee at least local optimality. The computational results indicate that the amount of improvement is statistically signi"cant for a set of randomly generated problems. The magnitude of cost savings is dependent on the system parameters

Dynamic lot sizing and tool management in automated manufacturing systems

The overall aim of this study is to show that there is a critical interface between the lot sizing and tool management decisions, and these two problems cannot be viewed in isolation. We propose five alternative algorithms to solve lot sizing, tool allocation and machining conditions optimization problems simultaneously. The first algorithm is an exact algorithm which finds the global optimum solution, and the others are heuristics equipped with a look-ahead mechanism to guarantee at least local optimality. The computational results indicate that the amount of improvement is statistically significant for a set of randomly generated problems. The magnitude of cost savings is dependent on the system parameters. In most of the studies on tool management, lot sizes are taken as a predetermined input while deciding on tool allocations and machining parameters. This might create empty feasible solution spaces and otherwise unnecessarily limit the number of alternatives possible for the tool management problem. In this study, we consider the integration of lot sizing and tool management problems ot minimize total production cost for multiple periods under dynamic demand. By integrating these decisions we not only improve the overall solution, but also prevent any infeasibility that might occur for the tool management problem due to decisions made at the lot sizing level. © 2002 Elsevier Science Ltd. All rights reserved

Feasibility study of an Integrated Program for Aerospace vehicle Design (IPAD). Volume 2: The design process

The extent to which IPAD is to support the design process is identified. Case studies of representative aerospace products were developed as models to characterize the design process and to provide design requirements for the IPAD computing system

Feasibility study of an Integrated Program for Aerospace-vehicle Design (IPAD) system. Volume 2: Characterization of the IPAD system, phase 1, task 1

The aircraft design process is discussed along with the degree of participation of the various engineering disciplines considered in this feasibility study

Trends and topics in IJPR from 1961 to 2017:a statistical history

This paper studies the history of the International Journal of Production Research (IJPR) by analysing the topics that have received the most attention in each of the journal’s publication years. Text mining exposed for scrutiny the most frequently mentioned and cited terms contained in the titles, abstracts and keywords of IJPR papers. Analyses suggest that the triad of scheduling/optimisation/simulation and supply-chain-related topics have been IJPR’s mainstays, but valuable opportunities remain for relevant topics that have not yet been concurrently and frequently studied. Results also show that terms related to sustainability and risk management topics have gained recent relevance. In addition, IJPR appears to complement its modelling technique focus with empirical methodological approaches to provide a well-balanced perspective, since the ‘case study’ term is common. Finally, a linear relationship is found between the number of papers that have covered certain topics and the number of citations those topics have received, highlighting which topics had fewer or more citations than expected, given the number of papers that covered those topics. IJPR stands as one of the most prestigious and established journals in its field and the results from this study indicate the evolving interests of the field for over half a century

Automating Business Process

Consistent presentation of the information is necessary to align stakeholders around the scope of the Program and formally gain their commitment. Reports play a major role in decision making and future planning for a financial teams and program directors. Generally, data is available when a transaction occurs and volume of data grows along with the organization. Maintaining historical and current data for reporting to stakeholders is a tough task and at times companies fail to report data accurately. Maintaining automated reporting for different modules of an organization in an ERP (Enterprise Resource Planning) system is one way of providing accurate data reporting to business. There are many tools in current day market to report data but SAP reporting tools provide a better solution according to business requirements. SAP Business Objects (SAP BO) is one of the leading SAP reporting tools that provide a complete pack of solution to the client. Since this organization already had a huge implementation of SAP Business Warehousing (SAP BW), implementing of SAP BO on top of SAP BW is a easy solution and cost effective too. As a part of this project, elimination of highly complex reporting and replacement of obsolete technologies was also considered

AI and OR in management of operations: history and trends

The last decade has seen a considerable growth in the use of Artificial Intelligence (AI) for operations management with the aim of finding solutions to problems that are increasing in complexity and scale. This paper begins by setting the context for the survey through a historical perspective of OR and AI. An extensive survey of applications of AI techniques for operations management, covering a total of over 1200 papers published from 1995 to 2004 is then presented. The survey utilizes Elsevier's ScienceDirect database as a source. Hence, the survey may not cover all the relevant journals but includes a sufficiently wide range of publications to make it representative of the research in the field. The papers are categorized into four areas of operations management: (a) design, (b) scheduling, (c) process planning and control and (d) quality, maintenance and fault diagnosis. Each of the four areas is categorized in terms of the AI techniques used: genetic algorithms, case-based reasoning, knowledge-based systems, fuzzy logic and hybrid techniques. The trends over the last decade are identified, discussed with respect to expected trends and directions for future work suggested

Energy-aware coordination of machine scheduling and support device recharging in production systems

Electricity generation from renewable energy sources is crucial for achieving climate targets, including greenhouse gas neutrality. Germany has made significant progress in increasing renewable energy generation. However, feed-in management actions have led to losses of renewable electricity in the past years, primarily from wind energy. These actions aim to maintain grid stability but result in excess renewable energy that goes unused. The lost electricity could have powered a multitude of households and saved CO2 emissions. Moreover, feed-in management actions incurred compensation claims of around 807 million Euros in 2021. Wind-abundant regions like Schleswig-Holstein are particularly affected by these actions, resulting in substantial losses of renewable electricity production. Expanding the power grid infrastructure is a costly and time-consuming solution to avoid feed-in management actions. An alternative approach is to increase local electricity consumption during peak renewable generation periods, which can help balance electricity supply and demand and reduce feed-in management actions. The dissertation focuses on energy-aware manufacturing decision-making, exploring ways to counteract feed-in management actions by increasing local industrial consumption during renewable generation peaks. The research proposes to guide production management decisions, synchronizing a company's energy consumption profile with renewable energy availability for more environmentally friendly production and improved grid stability