Basic structure of lessons learned approach to improve manufacturing processes: A case study

Networks of five-axis machine tools produce huge amounts of process data. These data directly reflect the running condition of the machine tool but are seldom used to examine the machine performance. This study proposes a new data acquisition method based on the Object linking and embedding for Process Control protocol without any additional monitoring equipment. The data collection principle is explained, and a client is developed based on the SIEMENS 840D system. Considering less influence on the manufacturing process, a communication architecture for the machine network is designed with a special computer transmitting the data to the server. A compression algorithm is applied to reduce the storage capacity of massive amounts of data. Finally, a method for predicting the future performance of the machine tool is proposed using similarity analysis of the time series. A Petri net model is also established to diagnose possible failure causes. These methods significantly improve the machine tool reliability and find potentially important information from the data in the manufacturing process.

RFID (radio frequency identification) is widely used in the manufacturing processes of enterprises. At the same time, with the advent of the Industry 4.0 era, Manufacturing Execution System (MES) systems began to evolve into cloud MES systems. In this paper, a RFID-based manufacturing process for cloud MES is proposed and a framework manufacturing process fora cloud MES system centered on machine tools is constructed. The process division of the manufacturing process, RFID configuration and cloud processing are analyzed, and other key technologies involved in implementing the framework are briefly discussed. Finally, the effectiveness of a RFID-based manufacturing process of cloud MES is verified by two different types of case analysis namely photovoltaic slice production and garment outsourcing processing.

The current condition, learning media in Manufacturing Process Design practicum still lacks teaching aids so that it cannot adjust its output according to industry needs. This needs to be improved to support industry-based learning. Before implementing teaching aids, the learning process was theoretical and did not involve students in real simulations, so their understanding of the manufacturing workflow was limited. This study aims to design and implement teaching aids in Manufacturing Process Design and Assembling practicums to support learning with the Learning Factory approach. The design of the teaching aids begins with observing the existing conditions, then determining the improvement plan through focus group discussions. After that, the design is carried out according to the needs of the practicum. The teaching aids made use a Programmable Logic Controller consisting of 4 stations. The use of designed teaching aids provides students with direct experience in the design and assembly process, and facilitates more interactive learning. The results of the study showed a significant increase in students' understanding of the manufacturing process, with more active involvement and an increase in the quality of assignments and practicum reports. These teaching aids have proven effective in creating a learning environment that is closer to real industrial conditions, so that they can improve students' competence in understanding manufacturing and assembly processes comprehensively.

The manufacturing stage is the core link of product reliability, and the manufacturing process control is the bridge between design reliability and product reliability. In the manufacturing process, the influence of various factors on the formation of product reliability is considered and controlled. Meanwhile, the process failure mode and impact analysis (PEMEA) method is introduced to clarify its principle and method. The key processes of the manufacturing and assembly process are identified by taking the RAT system of certain aircraft as an example. Effective measures are proposed to improve the manufacturing and assembly process, ensure the manufacturing reliability of products, and provide strong support for improving the quality and reliability of civil aircraft.

The purpose of this study was to improve the accuracy of three-axis CNC Milling Vertical engines with a general approach by using mathematical modeling methods of machine tool geometric errors. The inaccuracy of CNC machines can be caused by geometric errors that are an important factor during the manufacturing process and during the assembly phase, and are factors for being able to build machines with high-accuracy. To improve the accuracy of the three-axis vertical milling machine, by knowing geometric errors and identifying the error position parameters in the machine tool by arranging the mathematical modeling. The geometric error in the machine tool consists of twenty-one error parameters consisting of nine linear error parameters, nine angle error parameters and three perpendicular error parameters. The mathematical modeling approach of geometric error with the calculated alignment error and angle error in the supporting components of the machine motion is linear guide way and linear motion. The purpose of using this mathematical modeling approach is the identification of geometric errors that can be helpful as reference during the design, assembly and maintenance stages to improve the accuracy of CNC machines. Mathematically modeling geometric errors in CNC machine tools can illustrate the relationship between alignment error, position and angle on a linear guide way of three-axis vertical milling machines.

Aim: The internal market for manufacturers of consumer products companies is often too small in order to grant long-term success. Therefore, companies expand and enter foreign markets. This paper presents a planning process for market penetration for the selected foreign market, which will show the possibility of a withdrawal and shows also whether an exit scenario is planned by manufacturers of consumer products and when companies tend to think about a market exit.Design / Research methods: First, the literature was studied. Based on this, hypothesis were prepared. This was followed by a telephone survey of decision-makers from German manufacturers of the consumer products companies. Conclusions / findings: A planning process for market penetration was developed, which shows next to the market entry also the market exit. Additional this paper shows that manufacturers of consumer products companies can be better prepared for a market exit than companies without an exit strategy, in particular, if the manufacturer sets out relevant economic parameters for the foreign market which determine whether to remain in the market or leave.Originality / value of the article: When analysing literature on planning processes for market entry, it becomes clear that an exit strategy is not planned. This may indicate that the authors did not consider a market exit and/or anticipate this as a worst case in their market entry assumption.Implications of the research: The last market entry of the surveyed companies usually occurred recently. For market exit results to be determined, a further consultation of the companies examined should be undertaken over a longer period of time.

The development process of complex technical products of the last years shows an increasing amount of sensors, electronic control units, data logging and monitoring systems within consumer goods (e.g. automobiles, washing machines) and industrial goods (e.g. machine tools, manufacturing sys-tems). In many cases, the main goal of data logging is monitoring, controlling and optimisation of the product functionalities within the usage phase. A further aim is the fulfilment of the process capability of manufacturing processes. Therefore, the layout of the concept of operating data logging and monitoring systems—especially operating data (mainly type, volume, and format) as well as hardware (like sensors and storage)-is designed by the development engineer within the product concept development phase. This paper discusses challenges, requirements and approaches for future conceptual design of operating data logging concepts of technical products related to reliability engineering. Base of operations is the state of art. Based on that, the concept for operating data logging within a monitoring system is shown. The concept draft is subdivided in three parts which are divided as follows: part one deals with data analytics, part two contains data requirements, and part three focuses on hardware requirements. The presented research study was worked out on the international research platform “Computational Reliability Engineering in Product Development and Manufacturing (CRE) – 2017” and contains contributions of universities, institutes and original equipment manufacturers of industrial nations: Germany, United Kingdom, Japan, Turkey and France.

The surface waviness of the KH2PO4 crystal has important influence on its optical performance, but it is difficult to simulate by the current simulation models. This article presents an integrated machining performance forecasting method, which considers the interaction between manufacturing process and machine tool and integrates the cutting simulation, machine tool dynamic performance simulation and the control system. The profile and waviness prediction on the large area are achieved by this method with short time and high accuracy. The machining trials on a fly cutting machine tool are carried out to demonstrate the effectiveness of the proposed approach.

Utilization of Thermal Energy to Compensate Quasi-static Deformations in Modular Machine Tool Frames

The task of equipment testability design should be carried out during manufacturing process, to improve the diagnostic capabilities of equipment. According to the equipment testing requirements, equipment failure modes and effects analysis were completed, all possible failure modes of the equipment design and manufacturing process were ensured, as well as the causes and impact of each failure mode, whereby the equipment functions and structure were divided. Then, the relevance model was used for testability analysis and modeling of equipment in manufaturing process, relevance graphical model and mathematics model of component units related to equipment were builded, and the preferred method was used to consider the reliability and cost, the equipment diagnostic tree was builded, the equipment testing program was presented. A numerical example indicates that the study can effectively improve the efficiency of the equipment testing and enhance the economy of the test in manufaturing process.

A Study of Process Variability of the Injection Molding of Plastics Parts Using Statistical Process Control (SPC)Process variability in the manufacturing of products is a serious concern because if leftunchecked could lead to product wastes such as a scraps, low productivity, and poor qualityproducts. To prevent these unwanted effects from happening, statistical process control (SPC), astatistical tool, is used to monitor and control process variability. SPC assumes thatmanufactured products have measureable attributes such as mass, dimensions of the products,mechanical properties, and visual appearance to name a few. These attributes are affected bynatural and assignable causes. Natural causes are inherent to the process and may includevariables such as ambient temperature, machine vibration, and relative humidity; these variablesare often very difficult to control. Unlike natural causes, assignable causes are controllable andmay include items such as bad or worn-out machine components that should be replaced. Bymonitoring a process, an assignable cause is detected when process variability exceeds theexpected range caused by natural causes. The primary advantage of SPC is that it detects afaulty process, which if corrected, prevents the manufacturing of defective products unliketraditional quality control practice that identifies defective products after they have beenproduced. The traditional method of quality control leads to a costly manufacturing process.In a manufacturing engineering technology program, SPC was used to monitor and control theinjection molding of plastics parts. Students monitored several injection molding processvariables using SPC x-bar and range control charts while producing 300 plastics parts. The massof the products was used as an attribute representing parts quality. After analyzing the processdata, students were able to determine if the process was stable, that is, in control. Results of thisstudy will be presented at the annual conference. Also to be shared with the audience is thestudents' learning outcomes that emanates from integrating SPC with the injection moldingprocess.

A new geometric error modeling approach for multi-axis system based on stream of variation theory

A novel hybrid approach to explore the interaction among faults in production process with extended FMEA model using DEMATEL and cloud model theory

Effect of the composition and manufacturing process on the resin microtensile bond strength to ceramics

This paper presents a practical way in which current approaches to quality risk management (QRM) may be improved, such that they better support qualification, validation programs, and change control proposals at manufacturing sites. The paper is focused on the treatment of good manufacturing practice (GMP) controls during QRM exercises. It specifically addresses why it is important to evaluate and classify such controls in terms of how they affect the severity, probability of occurrence, and detection ratings that may be assigned to potential failure modes or negative events. It also presents a QRM process that is designed to directly link the outputs of risk assessments and risk control activities with qualification and validation protocols in the GMP environment. This paper concerns the need for improvement in the use of risk-based principles and tools when working to ensure that the manufacturing processes used to produce medicines, and their related equipment, are appropriate. Manufacturing processes need to be validated (or proven) to demonstrate that they can produce a medicine of the required quality. The items of equipment used in such processes need to be qualified, in order to prove that they are fit for their intended use. Quality risk management (QRM) tools can be used to support such qualification and validation activities, but their use should be science-based and subject to as little subjectivity and uncertainty as possible. When changes are proposed to manufacturing processes, equipment, or related activities, they also need careful evaluation to ensure that any risks present are managed effectively. This paper presents a practical approach to how QRM may be improved so that it better supports qualification, validation programs, and change control proposals in a more scientific way. This improved approach is based on the treatment of what are called good manufacturing process (GMP) controls during those QRM exercises. A GMP control can be considered to be any control that is put in place to assure product quality and regulatory compliance. This improved approach is also based on how the detectability of risks is assessed. This is important because when producing medicines, it is not always good practice to place a high reliance upon detection-type controls in the absence of an adequate level of assurance in the manufacturing process that leads to the finished medicine.