Manufacturability Trade-offs Research Articles

A review of sustainability trade-offs affecting suppliers in developed and less developed countries

PurposeThis paper aims to investigate the current state of research on sustainability-related manufacturing trade-offs (i.e. giving preference and priority to one dimension over others) that affect suppliers in developed and less developed countries (LDCs). There is growing pressure on suppliers to adopt sustainable practices into their global supply chains. Successfully implementing all three dimensions of the triple bottom line (TBL) imperative can provide organizations with an added capability and potentially result in competitive advantage and a focus on sustainable development goals (SDGs) in the long run. However, designing supply chains for achieving the TBL requires suppliers to recognize and overcome numerous trade-offs.Design/methodology/approachA systematic literature review comprising 71 papers published between 2004 and 2020 was undertaken using a content analysis approach to identify trade-offs affecting suppliers.FindingsThis study firstly identified eight sustainability-related trade-offs affecting suppliers from a TBL perspective in both developed and LDCs, consequently, allowing for a detailed discussion on trade-off factors and conditions unique to both developed and LDCs. Together, these findings enable this study to present initiatives and investment-related decisions for supply chains from a TBL perspective.Originality/valueIn spite of the plethora of studies on sustainable supply chains, there is little research on trade-offs, specifically those affecting sustainability of suppliers operating in LDCs. This paper addresses this critical gap and advances the literature on sustainability-related supply chain trade-offs.

Development of an Intelligent Tool Condition Monitoring System to Identify Manufacturing Tradeoffs and Optimal Machining Conditions

Abstract Smart manufacturing has leveraged the evolution of a sensor-based and data-driven platform to improve manufacturing outcomes. As a result of increased use of sensors and networked machines in manufacturing operations, artificial intelligence techniques play a key role to derive meaningful value from big data infrastructure. These techniques can inform decision making and can enable the implementation of more sustainable practices in the manufacturing industry. In machining processes, a considerable amount of waste (scrap) is generated as a result of failure to monitor a tool condition. Therefore, an intelligent tool condition monitoring system is developed in this paper to identify sustainability-related manufacturing tradeoffs and a set of optimal machining conditions by monitoring the status of the machine tool. An evolutionary algorithm-based multi-objective optimization is used to find the optimal operating conditions, and the solutions are visualized using a Pareto optimal front.

Improving trade-offs in manufacturing: Method and illustration

The analysis of trade-offs between competitive priorities is one of the core issues in manufacturing strategy research. However, past studies focused mainly on empirical validation of the trade-off concept. There has been limited research on practical aspects of trade-off management, especially methods for trade-off improvement and the incorporation of trade-off analysis into manufacturing strategy formulation. This study presents a heuristic method for the improvement of manufacturing trade-offs. The method incorporates the concepts of dynamic trade-offs and improvement trajectories into a decision-making process. An example of implementation is given, based on the case of a British manufacturer.

Thermal modeling of high performance packages in portable computers

An experimental and numerical study was conducted to determine the thermal performance of the Pentium(R) Processor in a tape carrier package (TCP) operating inside a typical portable computer. The objective of this study is to develop a validated system level model of the portable environment and demonstrate that equipment designers can carry out design iterations of possible heat transfer configurations to analyze cost, performance, and manufacturability tradeoffs. A detailed three-dimensional (3-D) numerical model of the package was constructed using a computational fluid dynamic software. In the interest of keeping the computational model tractable, some simplifying assumptions were employed to obtain equivalent compact models of the various components in the computer. The fluid motion is essentially a buoyancy driven convection inside an enclosure with multiple discrete heat sources. An experimental study was conducted to validate the numerical model. The results obtained indicate that the model is in good agreement with the experimental data, both qualitatively and quantitatively. Subsequent design iterations were conducted and thermal performance limits were established for various package families. The validated model was used to investigate design modifications to improve thermal performance through increased printed circuit board (PCB) thermal conductivity and the inclusion of heat spreaders, heat pipes, and vented enclosures.

Ion-implanted super-grain transistors

This paper discusses the use of ion implantation to develop a viable high-yielding process for fabricating super-gain transistors for integrated circuits. The authors discuss the fabrication processes utilized, the pertinent device physics, the manufacturing tradeoffs, and present the results obtained for two different ion-implanted base integrated-circuit processes.