Electronics Manufacturing Service Provider Research Articles

Enablers for Adopting Restriction of Hazardous Substances Directives by Electronic Manufacturing Service Providers

The Electronic Manufacturing Service (EMS) industry contributes significantly to toxic waste generation due to its fabrication processes. Notably, adherence to the Restriction of Hazardous Substances (RoHS) Directive varies amongst EMS providers, despite its aim to reduce electronic waste. This study explores the factors influencing EMS providers’ decision to adopt the RoHS directive, utilizing the technology–organization–environment (TOE) and the human–organization–technology (HOT) fit, or the TOE-HOT fit framework. We validated our framework using partial least squares structural equation modeling (PLS-SEM), based on responses from 379 questionnaires from major EMS providers. The results demonstrated that expert resources, adequate resources, perceived industrial pressure, institutional pressure, and costs were positively associated with RoHS adoption. However, innovation, relative advantage, and verification ability were identified as significant barriers. In particular, innovation in the human dimension was the key determinant for RoHS adoption. Therefore, clear policy instruments and regulations may enhance RoHS adoption by EMS providers. These findings can guide environmental policy definitions in governmental laws and strategies, encouraging EMS providers and other firms to adopt RoHS standards.

The Priority Order and Sensitivity Analysis of Mechanical System Failure Mode Improvement Based on Computer-aided

Failure mode is an analysis method used to determine potential failure modes and their causes. Specifically, through the implementation of FMEA, the weaknesses of the product can be found before the product design or production process is truly realized, and the product defects can be determined at the prototype stage or before mass production. FMEA is the first set of analysis mode formed by NASA. FMEA is a practical method to solve problems, which can be applied to many engineering fields. At present, many automobile manufacturers and electronic manufacturing service providers (EMS) in the world have adopted this mode to manage and monitor the design and production process. In the product design stage and process design stage, it is a systematic activity to analyze each process one by one, find out all potential failure modes, based on computer analysis of its possible consequences, and take necessary measures to improve product quality and reliability.

Design of receding-horizon estimators for the battery assembly system

Abstract The paper concerns the state estimation problem of a class of discrete-event systems. It is solved by defining a receding-horizon objective function that depends both on the prediction and output error. The system and its variables are described within the (max,+) algebra, which makes it possible to incorporate robustness within the overall framework. The paper also shows how to transform the interval cost function into the scalar one, and hence, making the computational procedure trackable within the quadratic programming framework. As a result, the proposed approach provided interval estimates of the system state, which can be used for both fault diagnosis and control purposes. An exemplary system is the battery assembly one, which is being designed and implemented in RAFI GmbH Company (one of the leading electronic manufacturing service providers in Germany). The final part of the paper shows illustrative examples, which exhibit the the performance of the proposed approach.

Performance assessment for electronic manufacturing service providers using two-stage super-efficiency SBM model

ABSTRACTManufacturing Service providers (EMSs) offer services to Original Equipment Manufacturers (OEMs). However, increasing challenges require an EMS to be more capable, adaptable and responsive. For survival, an EMS manager has to understand its relative efficiency in the industry. In addition, an investor also requires such information for investments. In this research, we propose a novel approach, which combines GM(1,1) with a two-stage super-efficiency slacks-based measure (SBM) model, to forecast and assess the efficiencies of 18 EMSs. The GM(1,1) was first used to forecast future data of EMSs, and then the two-stage super-efficiency SBM model was used to measure the marketability and profitability efficiencies for an EMU in two stages. The results build a ‘past-current-future’ view on the two efficiencies for each EMS. In addition, the profitability efficiency can help justify the reasonability of marketability efficiency. Our results showed that Hon Hai tops the rankings in both profitability and marketability efficiencies. These results also provided information about relative efficiencies of these EMSs, which helps EMS managers and investors to make better decisions.

A fault-tolerant approach to the control of a battery assembly system

The paper concerns fault-tolerant control of a real battery assembly system which is under a pilot implementation at RAFI GmbH Company (one of the leading electronic manufacturing service providers in Germany). The proposed framework is based on an interval analysis approach, which along with max-plus algebra, allows describing uncertain discrete event system such as the production one being considered in this paper. Having a mathematical system description, a model predictive control-based fault tolerant strategy is developed which can cope with both processing, transportation and mobile robot faults. In particular, it enables tolerating (up to some degree) the influence of these faults on the overall system performance. As a result, a novel robust predictive fault-tolerant strategy is developed that is applied to the advanced battery assembly system. The final part of the paper shows the implementation and experimental validation of the proposed strategy. The proposed approach is tested against single as well as simultaneous faults concerning processing, transportation and mobile robots.

Towards Robust Predictive Fault–Tolerant Control for a Battery Assembly System

Abstract The paper deals with the modeling and fault-tolerant control of a real battery assembly system which is under implementation at the RAFI GmbH company (one of the leading electronic manufacturing service providers in Germany). To model and control the battery assembly system, a unified max-plus algebra and model predictive control framework is introduced. Subsequently, the control strategy is enhanced with fault-tolerance features that increase the overall performance of the production system being considered. In particular, it enables tolerating (up to some degree) mobile robot, processing and transportation faults. The paper discusses also robustness issues, which are inevitable in real production systems. As a result, a novel robust predictive fault-tolerant strategy is developed that is applied to the battery assembly system. The last part of the paper shows illustrative examples, which clearly exhibit the performance of the proposed approach.

Lean transformation in a high mix low volume electronics assembly environment

Purpose – This paper aims to focus on integrating a lean framework in a high-mix-low-volume (HMLV) printed circuit board assembly (PCBA) environment to enhance current assembly processes and facility layouts. An HMLV PCBA environment is characterized by stochastic demands, a variety of products in terms of shapes and sizes and different sequences of assembly and test operations, in addition to long cycle times and high fall-out rates. Design/methodology/approach – Preliminary analysis indicates that the push inventory control system led to the longer cycle times, such that various lean methodologies have been applied to enhance the assembly operations. In this research, Kanban sizes for different assembly lines are also estimated to integrate and implement a “pull-system” into the lean framework. In addition, material movement and facility layout have been studied to minimize work-in-process travel time. An “iterative-MAIC” approach has been applied to implement lean principles. Findings – As a result, a lean manufacturing pilot line has been implemented to evaluate the effectiveness of the lean principles before rolling them out across the manufacturing floor. It has been shown that the cycle times of the pilot line products are decreased by 40 per cent and the number of defects decreased by 10-30 per cent, depending on different assembly processes, after the lean implementation. Originality/value – There is limited literature that addresses lean transformation in an HMLV electronics manufacturing service provider handling several product types with different testing methodologies, frequent product revision changes and higher fall-out rates. Hence, in this research, lean manufacturing has been implemented in an HMLV PCBA environment, which has the challenges of varying demand with a mix of assembly and test operations for different product families.

Collaboration and information sharing in global contract manufacturing networks

In the semiconductor and telecommunications industry original equipment manufacturers (OEMs) outsource manufacturing to contract manufacturers who are specialist electronic manufacturing service providers. There are a large number of such specialists in existence who collaborate with the original equipment manufacturers at one end and the component suppliers at another end and provide engineering, manufacturing and distribution services. But there do not exist good theoretical developments supporting these real world operations. We consider a global manufacturing system consisting of the contract manufacturer, logistics provider, and OEM and study the influence of sharing scheduling and demand information over the Internet. More specifically, we consider an OEM operating an Internet-based private exchange as a channel master with its contract manufacturers and their suppliers participating by sharing information. We develop a linear program based optimization model for this environment. Specifically, our LP model calculates the quantity of raw materials that is to be procured in each time period from each of the suppliers in order to meet the given demand. We compare these results with traditional make-to-stock linear supply chains with sequential order flow. Our numerical experiments show that information sharing results in cost and inventory reduction.