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Electrical defects cover an important part of assembly defects and strongly affect the vehicle system performance. Almost 40% of assembly defects are classified as human errors and electrical connection failures represent a significant part of them. Humans still remain a cost-effective solution for the flexible manufacturing systems with increasing product complexity. So, understanding human behaviors is still a challenging task. The purpose of this study is to define, prioritize and validate the critical factors for the complexity of electrical connector plugin process.

The critical variables were defined by the expert team members. The required number of measurements and variables were revised resulting preliminary analysis of binary logistic regression. After the revision of measurement plan, the list of critical input variables and the mathematical model were defined. The model has been validated by the fitted values of the residuals (FITS analysis).

To the best of the authors’ knowledge, this is one of the limited studies, which defines the critical factors for electrical connection process complexity. Female connector harness length, connector width/height/length differences, operator sense of correct connector matching and ergonomy were defined as the factors with the highest impact on the failure occurrence. The obtained regression equation strongly correlates the failure probability.

The obtained mathematical model can be used in new model development processes both for the product and assembly process design (ergonomy, accessibility and lay-out).

The obtained risk factors demonstrated a strong correlation with assembly process complexity and failure rates. The output of this study would be used as an important guide for process (assembly line ergonomy, accessibility and lay-out) and product design in new model development and assembly ramp-up phases.

In the electrical industry 50 to 75% of the total production costs of a product are in assembly. This shows that the main focus for rationalisation should be in assembly. This paper illustrates planning methods for rationalisation, describes a completed assembly line and outlines the economies obtained.

Analysis of test data monitored for a number of electric machines from the low volume production line can lead to useful conclusions. The purpose of this paper is to trace the machine performance to find quality-related issues and/or identify assembly process ones. In this paper, the monitoring of experimental data is related to the axial flux motor (AFM) used in hybrid electric vehicle (HEV) and in electric vehicle (EV) traction motors in the global automobile market.

Extensive data analyses raised questions like what could be the causes of possible performance deterioration of the AFM and how many electric motors may not pass requirements during operation tests. In small and medium research units of AFM for HEV or EV, engineers came across a number of serious issues that must be resolved. A number of issues can be eliminated by implementing methods for reducing the number of failing AFMs. For example, improving the motor assembly precision leads to reduction of the machine parameters deterioration.

Assembly tolerances on electric motor characteristics should be investigated during motor design. The presented measurements can be usable and can point out the weakest parts of the motor that can be a reason for the reduced efficiency and/or lifetime of the AFM. Additionally, the paper is addressed to electric motor engineers designing and/or investigating electric AFMs.

Performance of AFM was monitored for a number of identical motors from low volume production line. All tested motors were operated continuously for a long period of time and the tests were repeated every few weeks for half a year to check the reliability of motor design and indicate how much the motor parameters may change. The final results point how many motors fail the requirements of motor performance. A few batches of AFM were selected for testing. Each batch represents a different size (nominal power) of the same type of AFM.

The management of materials consists of an important analysis for industries as there are factors in several areas that should be considered. For this, it should take into account logistical factors, quality and production, because one piece delivered in a large lead time or outside the technical quality standards, imply delays in the project or rework. In this context, the importance of creating a control method of input and output of tools in an aviation industry in the city of Toulouse, France, was seen due to the amount of many incomplete arrivals or inappropriate material for use. The paper aims to discuss this issue.

This study used a philosophy of lean manufacturing tools and visual management (VM). A VM panel with information documents of all tools used in an assembly station of a model airplane was applied. With all data collected to carry out the project, the panel was created with the most relevant information of each tool and applied to an assembly station. That done, the production supervisors, mechanical and electrical supervisors were trained in the operation. Despite a change of management, it was realized that all supported the change due to the ease of understanding of the method and a good VM.

At the end of the work, materials management became more simplified, operators were more satisfied because of the non-occurrence of tools mistakes and the control time decreased from 120 to 15 minutes.

The application of this project has begun in an assembly station; however, it has been validated to be applied throughout the facility and its applications are being studied for other industries with different models.

This project developed a visual panel for support visual communication of the airplane assembly line. Its usage eliminates tools lost, inefficiencies and decreases lost time with tools selection.

This work proposes a way to simplify the management tools for assembly station plane using a VM panel based on the lean philosophy. The study was conducted at the Final Assembly Line of an aircraft model from a unit of an aircraft company.

This paper presents a novel mesoscale RF (mRF) relay that integrates advanced high resolution stereolithography (SL) and micro wire electro discharge machining (μEDM) technologies. Methods and infrastructure for reliable batch assembly of electromechanical actuators and structural parts less than 5 mm³ in volume are described. Switches made using these techniques are expected to have greater power handling capability relative to current micro RF relay products.

The conjecture is that the integration of SL and similar rapid additive manufacturing with other mesofabrication technologies can yield innovative miniature products with novel capabilities. A series of mRF prototypes consisting of a contact mechanism and actuator with return spring were fabricated assembled, inspected, and characterized for electromechanical performance. Characterization results led to specific conclusions regarding capabilities of the mRF product, and the integrated manufacturing technique.

The microassembly apparatus and epoxy‐based fastening system led to durable prototypes within 4 h (excluding a 16‐24 h cure cycle). Relay stroke ranged from 560 to 1,650 μm indicating a relative assembly accuracy of 90 percent. Prototypes demonstrated insertion loss of 1.3 dB at 100 MHz and isolation of better than 30 dB through 300 MHz.

Results indicated that fully functional and robust mesoscale relays are possible using integrated manufacturing with SL. However, prototypes exhibited high contact resistance and lacked assembly precision in the context of contact mechanism stroke. Opportunities exist to reduce contact resistance and switching time.

The research provides a practical new product application for integrated mesoscale rapid manufacturing.

This work represents one of the first examples of a mesoscale relay rapidly manufactured with a combination of μEDM and SL components.

THE German Diehl Group has divisions producing: non‐ferrous metal products; clocks and watches; control systems; industrial machinery; ammunition; and track systems. It employs a total of more than 13,000 people.

In this, the second part of a two‐part paper (Part I, Personnel Review, Summer 1977, pp 21–34) a survey of instances of work system design (WSD) experiments will be continued. As described in the Introduction to Part I, cases chosen for inclusion report the economic and human results of actual physical or structural innovations in a set or series of human tasks which, taken together, form some meaningful technical whole. The term ‘experiment’ is used in both Part I and II to refer loosely to change or manipulation of actual work activities, and not necessarily to well controlled laboratory experiments. In fact, most cases reported here are ‘natural’ and very few are carefully controlled.

Describes how engineers from Lockheed Martin, USA, reduced the weight and power draw of an oscillator in an aircraft electrical assembly by using computational fluid dynamics to optimize radiative and natural convective cooling, thereby eliminating the need for a fan within the assembly.

The purpose of this paper is to improve the failure analysis and troubleshooting process in engineering to order (ETO) product development, and reduce the amount of parts with failures. This is important because parts with failures are associated with the additional costs resulting from corrections of the product, reduced productivity due to the time waiting for the corrected part, delays in delivery and harm to the image of the organization.

FMEA and A3 are combined in a document for failure analysis and recording of the generated knowledge. The method is applied to an industrial automation company that designs and manufactures ETO products. Initially, the failures identified in mechanical assembly products are mapped, and then FMEA and A3 are combined in a document template, and a checklist for reviewing the detailing is built. Then, the method is applied in the design phase, and also for solving conceptual failures in the mechanical assembly and testing phase and the knowledge generated is recorded.

The results show the feasibility of the proposed method for both failure analysis and knowledge generation. Moreover, the adoption of improvement practices in routine activities, for example, the checklist for reviewing the detailing, can reduce up to 10 percent the amount of parts with failures.

The integration of FMEA and A3 encourages group thinking and monitoring the implemented actions. Since the document contains minor changes in the layout from the design phase to the assembly and testing phase, it contributed to the understanding of the people who participated in performing each phase. It should be ensured that the participation of experienced individuals with a proactive assertiveness who encourage the exchange of knowledge, preventing recurring failures from occurring in the conceptual phase. The approach to ensure quality was well accepted by the personnel in the company, but the implementation requires changing habits and establishing new practices.

The method proposed in this paper was applied to a company that designs and manufactures ETO industrial automation products. Since such products have high variety, the company has different characteristics compared with the companies that were considered in the few publications that attempted to combine the FMEA and A3 methods for failure analysis. The proposed method provides convenience for queries and updates, since it allows the inclusion of different failures in a single A3 report, reducing the number of separate documents. Also, the method includes a checklist for detailing review, which contributed to the reduction of failures.

In the automotive industry, the high process complexity becomes an important issue because of the increased number of product and process variants demanded by the customers. To avoid quality defects in assembly and losses in such a complex manufacturing environment, new predictive support systems are required. This study aims to develop a multiple attribute decision support system (DSS) for the prediction and quantification of the risk of failures on the workstations of a leading Turkish automotive manufacturing company.

Initially, the factors affecting the failures in workstations and the attributes to evaluate the factors are identified. Subsequently, the relations among the attributes are specified and priorities of them are calculated. Finally, the risk of failures is calculated and tested in a pilot study and validated with real production data.

To the best of authors’ knowledge, this is a unique study that computes the risk scores on the workstations via DSS. The DSS has various advantages for improvements of the manufacturing quality: the risk of failures can be detectable and comparable, the effect of changes in the design of new workstations can be observed. Stations that have medium or high complexity scores demonstrated strong correlation with failure rates. A sensitivity analysis is conducted to predict the effect of improvement actions on the riskiness of the workstations.

High level of production complexity becomes a crucial issue for companies that use various production processes. Considering this fact, it is a requirement for companies to observe and monitor the risk factors, especially in the assembly lines to be able to eliminate failures derived from complexity. Accordingly, to measure risk scores of the workstations in the assembly lines, a decision support for companies aids executives to manage the complexity level in a reliable and effective way. In this study, the authors develop such a DSS for TOFAS, a leading Turkish automotive company. The proposed DSS is verified and applied through a pilot study on a specific basic production unit. A sensitivity analysis is also conducted to see the effects of potential improvements on the risk scores. Additionally, the trend of risk scores for the stations can also give valuable information for tracing the changes in the time horizon. The proposed DSS also enables an opportunity for the executives in their decision of design processes of new production lines by allocating limited resources in an appropriate way based on the risk scores of possible workstations. The proposed DSS is the first and unique proactive failure prevention model developed in a Fiat Chrysler Automobiles (FCA) plant across the world. TOFAS executives also plan to introduce and enlarge the usage of the model to other FCA plants. It may also be possible to apply the model to other assembly lines in any sector. Another plan of the executives of TOFAS is developing a software, which manages each parameter, to constitute data to the DSS to run this system more instantly and effectively. Moreover, they can take integration actions of the software with world-class manufacturing problem management system that is currently in use in TOFAS.