A framework of justification criteria for advanced manufacturing technology implementation in small and medium enterprises

Today in order to stay in businesses and prosper, Small and Medium Enterprises (SMEs) are seeking higher electiveness and competitiveness across the entire cycle of marketing, product design, manufacture, test and sales. SMEs play an increasingly important role in all aspects of competitiveness: both products and production techniques, but also management methods, the organization of the firm and human resources training. One of the ways by which SMEs can achieve a competitive advantage in manufacturing is through the implementation of Advanced Manufacturing Technology (AMT). An increasing number of them have chosen and are choosing various levels of AMT as the solution. Realizing the importance of SMEs, an attempt has been made in this paper to review the application of AMT in SMEs. Also, a framework has been offered for the implementation of AMT in SMEs. Finally, a summary of findings and conclusions are presented

ARMD Workshop on Materials and Methods for Rapid Manufacturing for Commercial and Urban Aviation

This report documents the goals, organization and outcomes of the NASA Aeronautics Research Mission Directorates (ARMD) Materials and Methods for Rapid Manufacturing for Commercial and Urban Aviation Workshop. The workshop began with a series of plenary presentations by leaders in the field of structures and materials, followed by concurrent symposia focused on forecasting the future of various technologies related to rapid manufacturing of metallic materials and polymeric matrix composites, referred to herein as composites. Shortly after the workshop, questionnaires were sent to key workshop participants from the aerospace industry with requests to rank the importance of a series of potential investment areas identified during the workshop. Outcomes from the workshop and subsequent questionnaires are being used as guidance for NASA investments in this important technology area

Integrating Multiobjective Optimization With The Six Sigma Methodology For Online Process Control

Over the past two decades, the Define-Measure-Analyze-Improve-Control (DMAIC) framework of the Six Sigma methodology and a host of statistical tools have been brought to bear on process improvement efforts in today’s businesses. However, a major challenge of implementing the Six Sigma methodology is maintaining the process improvements and providing real-time performance feedback and control after solutions are implemented, especially in the presence of multiple process performance objectives. The consideration of a multiplicity of objectives in business and process improvement is commonplace and, quite frankly, necessary. However, balancing the collection of objectives is challenging as the objectives are inextricably linked, and, oftentimes, in conflict. Previous studies have reported varied success in enhancing the Six Sigma methodology by integrating optimization methods in order to reduce variability. These studies focus these enhancements primarily within the Improve phase of the Six Sigma methodology, optimizing a single objective. The current research and practice of using the Six Sigma methodology and optimization methods do little to address the real-time feedback and control for online process control in the case of multiple objectives. This research proposes an innovative integrated Six Sigma multiobjective optimization (SSMO) approach for online process control. It integrates the Six Sigma DMAIC framework with a nature-inspired optimization procedure that iteratively perturbs a set of decision variables providing feedback to the online process, eventually converging to a set of tradeoff process configurations that improves and maintains process stability. For proof of concept, the approach is applied to a general business process model – a well-known inventory management model – that is formally defined and specifies various process costs as objective functions. The proposed iv SSMO approach and the business process model are programmed and incorporated into a software platform. Computational experiments are performed using both three sigma (3σ)-based and six sigma (6σ)-based process control, and the results reveal that the proposed SSMO approach performs far better than the traditional approaches in improving the stability of the process. This research investigation shows that the benefits of enhancing the Six Sigma method for multiobjective optimization and for online process control are immense

Integrated production quality and condition-based maintenance optimisation for a stochastically deteriorating manufacturing system

This paper investigates the problem of optimally integrating production quality and condition-based maintenance in a stochastically deteriorating single- product, single-machine production system. Inspections are periodically performed on the system to assess its actual degradation status. The system is considered to be in ‘fail mode’ whenever its degradation level exceeds a predetermined threshold. The proportion of non-conforming items, those that are produced during the time interval where the degradation is beyond the specification threshold, are replaced either via overtime production or spot market purchases. To optimise preventive maintenance costs and at the same time reduce production of non-conforming items, the degradation of the system must be optimally monitored so that preventive maintenance is carried out at appropriate time intervals. In this paper, an integrated optimisation model is developed to determine the optimal inspection cycle and the degradation threshold level, beyond which preventive maintenance should be carried out, while minimising the sum of inspection and maintenance costs, in addition to the production of non-conforming items and inventory costs. An expression for the total expected cost rate over an infinite time horizon is developed and solution method for the resulting model is discussed. Numerical experiments are provided to illustrate the proposed approach

Integrating the Cost of Quality into Multi-Products Multi-Components Supply Chain Network Design

More than ever before the success of a company heavily depends on its supply chain and how efficient the network. A supply chain needs to be configured in such a manner as to minimize cost while still maintaining a good quality level to satisfy the end user and to be efficient, designing for the network and the whole chain is important. Including the cost of quality into the process of designing the network can be rewording and revealing. In this research the concept of cost of quality as a performance measure was integrated into the supply chain network designing process for a supply chain concerned with multi products multi components. This research discusses how this supply chain can be mathematically modeled, solutions for the resulted model and finally studied the effect of the inclusion of the quality as a parameter on the result of the deigning process. Nonlinear mixed integer mathematical model was developed for the problem and for solving the model two solutions based on Genetic algorithm and Tabu Search were developed and compared. The results and analysis show that the solution based on the Genetic algorithm outperforms the Tabu Search based solution especially in large size problems. In addition, the analysis showed that the inclusion of the cost of quality into the model effect the designing process and changes the resultant routes

Disparate data integration case for connected factories using timestamps

Manufacturing data integration of machine, process, and sensor data from the shop floor remains an important issue to achieve the anticipated business value of fully connected factories. Integrated manufacturing data has been a hallmark of Industry 4.0 initiatives, because integrated data precipitates better decision-making for cost, schedule, and system optimizations.  In this paper, we extend work on optimizing manufacturing costs, describing an algorithm using timestamps to integrate previously unassociated quality and test information, enabling us to better identify and eliminate redundant tests.  Results are provided and discussed, and we suggest the approach described may be valuable for some types of heterogeneous manufacturing data integration where timestamps and event chronologies are available

Application of digital technology in TQM business processes

Abstract: TQM (Total Quality Management) has become the world`s dominant quality solution in improving quality systems and continuous improvement. Industries are using the ISO 9001 standard for compliance, while other organizations practice TQM to further develop and sustain the organizational strategic goals and income growth. The revelation on the application of a quality management system and ISO 9001 has by far been the quality requirement from customers and regulators as evidence of commitment and ability of every organization. Various industries have implemented TQM to advance their quality systems in order to control and better the organizational culture. Competition within industries indicated the importance of customer satisfaction for corporate profitability and survival, where quality has become the key factor for the survival and competitiveness of a business [1]. Currently all industries have become competitive. According to Hendricks and Singhal [2], firms that have effectively implemented Total Quality Management outperform firms within the same level caliber that have not implemented total quality management in terms of cost, income, profits, total assets, number of resources and capital outlay. Aleksandrova, Vasiliev, Letuchev [3], emphasized on the integration of quality management methods with modern information technology that it may ensure competitiveness in existing organizations. Total Quality Management has only been applied in manufacturing industries but has over the years evolved into diverse business sectors to gain reputation as the main factor to achieve competitive advantage...M.Ing. (Engineering Management