Unit Process Life Cycle Inventory Research Articles

Reusable unit process life cycle inventory for manufacturing: high speed laser directed energy deposition

The unit process life cycle inventory is a modeling approach to estimate the energy demand and resource requirements of a unit process. Thus, a model of the unit process life cycle inventory for a specific manufacturing process can be used for quantifying the environmental impacts of specific products manufactured by that process. Within the approach, reusable models are developed for specific manufacturing processes. In this paper, the development and validation of a unit process life cycle inventory model for high-speed laser directed energy deposition is presented. This additive manufacturing process offers great potential for the industry due to its fast process speed. However, high-speed laser directed energy deposition has a high energy consumption and resource demand. Assessing the energy demand for individual manufactured products is a time-intensive process that requires expert knowledge. Thus, the development of an adaptable unit process life cycle inventory model enables more convenient assessment and improvement of its energy and resource efficiencies for producing different products. For the development of the model, the subsystems of a high-speed laser directed energy deposition machine are analyzed separately, e. g. the laser generator, the trajectory system, the powder feeder, and the suction system. Afterward, the energy and material demand of these subsystems are described in mathematical models. Finally, the model is validated by comparing the energy demands of three demonstration parts, measured by experiments, and predicted by the model.

Comparative LCA of automotive gear hobbing processes with flood lubrication and MQL

The life cycle inventory (LCI) data of a gear hobbing was obtained by means of the methodology unit process life cycle inventory (UPLCI), to conduct a comparative life cycle assessment (LCA) between hobbing assisted by flood lubrication (FL) and minimum quantity lubrication (MQL). The results pointed out 4 among 11 normalized environmental impact categories totalized more than 80% of the accumulated impacts: Fossil Depletion (43%), Climate Changes (19%), Terrestrial Acidification (11%), and Freshwater Consumption (8%). The identified hotspot in the case study was the input flow of raw material for the system “Hobbing Machine,” which was linked to more than 75% of the total amount of normalized potential environmental impacts. Once, changes on raw material depends on the gear design, the research focused on the environmental aspects of energy and cutting fluid consumption, which depends directly on the hobbing process parameters. The introduction of MQL provided reduction of 70.77% on the total amount of normalized potential impacts, while the strategies to reduce electric energy consumption by the machine tool accounted only for 3.74%. Nevertheless, when raw material flow is considered in the LCA, it turns into the process hotspot, due to high energy demanded in the steel-making process, forging, and turning operations to shape the semi-finished gear. The relevance of the key environmental aspects, electric energy, cutting fluids, and raw material, can vary significantly according to the gear size itself. The performed case study was considered a pilot project for the hosting company and can be scaled up to a whole gear manufacturing plant to identify manufacturing cells, which are eligible to optimization in the use of cutting fluids and electric energy by the machine tools.

Comparative LCA of conventional manufacturing vs. additive manufacturing: the case of injection moulding for recycled polymers

ABSTRACT Additive Manufacturing helps to develop production alternatives with new technologies and less environmental impacts. The comparative analysis was performed between two manufacturing processes using black recycled Acrylonitrile Butadiene Styrene (ABS) pellets to evaluate the potential environmental impacts between Injection moulding and Fused Deposition Modelling (FDM). The Life Cycle Assessment (LCA) and the Unit Process Life Cycle Inventory (UPLCI) methodology were adopted, which resulted in an impact assessment separated by operation modes and subunits of the equipment. The LCA results indicate a lower environmental impact of the FDM when the aim is to produce a batch size smaller than 14 parts. For batch sizes above 50 parts, the Injection moulding process generated less impact to the Global Warming Potential (GWP) and Cumulative Energy Demand (CED). The printing stage contributed the most to generating impacts for the FDM. In the Injection moulding process, the main responsible for generating impacts were the injection phase. Mechanical tensile tests were carried out with the parts obtained by the FDM with different infills (25%, 50%, 75% and 100%), and it was observed that parts with 100% infill obtained the best relation between mechanical properties and environmental impacts.

Machine-Specific Estimation of Milling Energy Consumption in Detailed Design

AbstractManufacturing is a significant contributor to global greenhouse gas emissions and there is an urgent need to reduce the energy consumption of production processes. An important step towards this goal is proactively estimating process energy consumption at the detailed design stage. This is a challenging task as variabilities in factors such as process specifications, machine tool architecture, and workpiece geometry can significantly reduce the accuracy of the estimated energy consumption. This paper discusses a methodology for machine-specific energy estimation in milling processes at the detailed design stage based on the unit process life cycle inventory (UPLCI) model. We develop an adjusted UPLCI model that includes adjustment factors for uncertainties in machine tool specifications and the specific cutting energy of a workpiece material. These adjustment factors are calculated through experimental measurement of energy consumption for a reference test part on a specific machine tool. To validate the adjusted UPLCI model, we conducted a case study that measured the energy consumption for machining three parts made of Aluminum 6082 on two separate three-axis vertical milling machines, a Chevalier QP2040-L and a Leadwell MCV-OP. Results show that the UPLCI model consistently overestimated the total energy consumption for machining the three validation parts across both machine tools. We also found that the adjusted UPLCI model significantly reduced the estimation errors for the same tests for both machine tools.

Energy consumption model of plasma spraying based on unit process life cycle inventory

Plasma spraying is an energy intensive manufacturing process to provide function coatings. As such, energy consumption analysis always is promising for the development of green plasma spraying. In this study, a systematic energy consumption model of plasma spraying was presented considering various working states and processing parameters with unit process life cycle inventory method. Verification showed that energy consumption could be accurately calculated with this model within 5% errors. In light of this model, an L9 Taguchi test was carried out to investigate the relationship between energy consumption and coating quality (i.e., coating thickness, hardness, and porosity) with different processing factors (i.e., power, powder feeding rate, spraying jet velocity, and scanning step). It was indicated that power was the most influential factors for the energy consumption and the following factors were scanning step and spraying jet velocity. Besides, Energy analysis showed that the coating thickness and hardness are closely related to the unit energy consumption with a linear and quadratic function respectively. This work provides a basic guidance for quantifying energy consumption and could be extended for the sustainable development of plasma spraying.

Reusable unit process life cycle inventory for manufacturing: metal injection molding

Unit process life cycle inventory (UPLCI) is a modeling approach that enables researchers to estimate the energy use and material flow for a unit process. UPLCI models can be reused in characterizing a full manufacturing line, where a wide range of machines and materials are used. As part of a collaborative effort from various universities and industry researchers to create UPLCI models for all common manufacturing processes, this paper presents UPLCI for the metal injection molding (MIM) process, which is in the mass conserving category of the taxonomy of manufacturing processes. In addition to the energy required for injection molding of the metal-polymer feedstock and for the subsequent debinding and sintering processes, the energy consumption during idle and standby periods are also captured. The application of the UPLCI model for MIM process is demonstrated using an example case study. This UPLCI model provides opportunity for researchers to estimate the energy use for a sequence of manufacturing processes used to make a metal injection molded product.

Life cycle assessment of a hot-pressing machine to manufacture particleboards: hotspots, environmental indicators, and solutions

Green manufacturing (GM) is the environmental benign manufacturing of products with a minimal negative impact on the natural environment. Research studies on GM have increased in the last years with attention to the application of life cycle assessment (LCA). However, the manufacturing industry still faces some barriers and challenges that hinder a proper practical integration of GM using LCA. Accordingly, this paper performs an LCA-based GM case study of a wood-based industry that produces particleboards to investigate environmental hotspots and suggests GM indicators and solutions for a hot-pressing machine tool. A case study of a wood-based industry that produces particleboards in Brazil was designed. A LCA-based GM framework was developed and applied according to its three phases: pre-assessment, environmental assessment and monitoring, and post-assessment. Each phase is composed of specific stages and each stage has its own activities and goals. To quantify the environmental life cycle impacts, the ILCD midpoint method with 13 impact categories was selected. Based on these environmental impacts, a set of indicators and solutions was designed to improve the product life cycle impacts through a greener manufacturing process of particleboards. A cradle-to-grave approach was used to model the particleboard life cycle and the manufacturing phase was modeled based on the unit process life cycle inventory (UPLCI) methodology. The particleboard manufacture was designed into five unit processes and results of the pre-assessment showed that the hot-pressing unit was the most relevant process because of its direct and indirect impacts mainly to human toxicity cancer effects, global warming, and photochemical ozone formation. During the environmental assessment and monitoring phase, the hot-pressing machine was then investigated based on the main contributors to the caused environmental impacts, i.e., electricity consumption and air emissions of free formaldehyde, as well as in terms of its most relevant process parameters: pressure (P) and temperature (T). Opportunities to reduce up to 21% upstream impacts and up to 41% downstream impacts were identified from making simple changes to the hot-pressing parameters. Further investigation in the post-assessment revealed that environmental impacts can be estimated based on the applied P and T values and GM indicators were suggested. The proposed GM framework can be used in other case studies to integrate GM + LCA in practice. Results of the case study application showed that the hot-pressing machine was a hotspot into the cradle-to-grave life cycle impacts of particleboards and the proposed GM indicators can be used to predict life cycle impacts at manufacturing level.

Reusable unit process life cycle inventory for manufacturing: stereolithography

Additive manufacturing technologies have been implemented in a variety of industries such as aerospace, automotive, healthcare, and military. The increasing application is owing to the unique capability of AM for fabricating parts layer by layer. Compared to traditional manufacturing processes, AM can achieve enhanced design and manufacturing complexity. In addition, it has been argued that AM could also reduce the environmental footprint of a product. However, recent studies reveal that AM processes may cause environmental consequences. Characterization of manufacturing processes for their environmental performance can be achieved by evaluating input and output material and energy flows. The unit process life cycle inventory methodology is a promising approach to develop reusable models and tools to calculate these flows. The unit process life cycle inventory models can be connected to estimate the total material/energy consumption of and emissions from product manufacturing based on a process plan. In this paper, we develop a unit process life cycle inventory model for one of the most widely used additive manufacturing processes i.e., Stereolithography, which fabricates parts by using ultraviolet light to solidify the photosensitive liquid resin in a matter of seconds layer by layer. The model is constructed with the knowledge of physical and chemical principles and is based on production information and equipment specifications. A case study is provided to demonstrate how to use the unit process life cyle inventory model on Stereolithography.

Reusable unit process life cycle inventory for manufacturing: gas metal arc welding

The paper develops a unit process life cycle inventory (UPLCI) for gas metal arc welding (GMAW) process. UPLCI is a modeling approach that allows users to estimate the energy and materials flow of a unit process. A UPLCI model can be reused in different manufacturing settings where a wide range of machines and materials are used. GMAW is in the joining category of the taxonomy of manufacturing processes, and this work is part of the effort to build UPLCI models for all common manufacturing processes. Following UPLCI approach, the energy consumption is not limited to the energy needed to initiate and maintain the arc (i.e. active energy). Energy spent during idle and standby are also accounted. An example calculation is provided to demonstrate how the GMAW model can be used. It should be noted that the GMAW model can be linked to UPLCI models of other unit processes. This makes it possible to estimate the materials loss and energy use (thus environmental impacts) of a product made by a sequence of manufacturing processes.

Reusable unit process life cycle inventory for manufacturing: grinding

This paper is a part of a series in which the goal is to provide users with calculation tools to estimate the energy use and mass loss of one unit process in a full manufacturing line. It is known as a unit process life cycle inventory (UPLCI). As such, this information is reusable in a wide range of products made of different materials. Grinding is the first UPLCI in this series, which is in the mass reduction category of the taxonomy of manufacturing processes. The energy calculations are not limited to the active or tip grinding energy, but include idle and basic energy values. In addition, an example calculation is provided to assist the UPLCI reader. The UPLCI can then be connected to others to estimate whole product manufacturing sequences.

Ascertaining Life Cycle Inventory Data for Electrical Discharge Machining

Sustainable manufacturing systems require accounting for both product and process level environmental impacts. Established methods and databases are available for product level environmental impact assessment. However, there is a lack of data for process level or use phase assessments despite these being responsible for a significant share of the total environmental impact. This lack of data is even further exacerbated for unconventional machining (UCM) - unit process Life Cycle Inventory (LCI) data for UCM processes has particularly limited records in LCI databases. Electrical discharge machining (EDM), which is the most widely used UCM process, is reported as much less energy efficient compared to conventional machining processes. In addition to that, EDM produces wastes in solid, liquid, gas and aerosol form increasing its environmental footprint. The purpose of this study is to ascertain LCI data for EDM processes and thus to facilitate improved life cycle assessment during the use phase. The study takes insights of CO2PE!-methodology, a systematic inventory analysis of the use phase of manufacturing unit processes. Case studies are carried out with an industrial die and mould manufacturer. The resultant data for die sinking and wire EDM is then compared with publicly available data. Challenges of generalising LCI data are discussed with future improvement potentials.

Prediction of unit process life cycle inventory (UPLCI) energy consumption in a friction stir weld

The objective of this study is to determine a method of quantifying the energy consumption in friction stir welding (FSW). Qualitatively, it has long been known that FSW uses less energy than fusion welding processes because the average FSW weld temperature does not exceed the solidus temperature. However, tools and data to quantitatively determine the energy consumption in FSW have been missing. The power consumption as a function of time was measured during FSW of 5.2-mm-deep welds in 6061-T6 and 7075-T6 aluminum alloys on a 3-axis CNC mill. The energy consumption is divided into four parts: idle energy and standby energy related to the machine being used as well as plunge energy and FSW energy related to creating the joint. Equations for calculating each of the energy components and the total energy consumption are presented. The concept of specific weld energy is presented as an intrinsic material property that can be used to estimate the FSW power if the weld cross-section and weld speed are known. A method of estimating the weld cross-section based on the FSW tool geometry is presented. It is found that for these two aluminum alloys the specific weld energy decreases significantly with increased weld speed, however, it can be treated as independent of spindle rotation rate. The FSW process/machine is identified as low tare and it is acknowledged that the strategies to reduce total energy consumption may be different than those used for metal cutting.

Methodology for systematic analysis and improvement of manufacturing unit process life cycle inventory (UPLCI) CO2PE! initiative (cooperative effort on process emissions in manufacturing). Part 2: case studies

This report presents two case studies, one for both the screening approach and the in-depth approach, demonstrating the application of the life cycle assessment-oriented methodology for systematic inventory analysis of the machine tool use phase of manufacturing unit processes, which has been developed in the framework of the CO2PE! collaborative research programme (CO2PE! 2011) and is described in part 1 of this paper (Kellens et al. 2011). The screening approach, which provides a first insight into the unit process and results in a set of approximate LCI data, relies on representative industrial data and engineering calculations for energy use and material loss. This approach is illustrated by means of a case study of a drilling process. The in-depth approach, which leads to more accurate LCI data as well as the identification of potential for environmental improvements of the manufacturing unit processes, is subdivided into four modules, including a time study, a power consumption study, a consumables study and an emissions study, in which all relevant process in- and outputs are measured and analysed in detail. The procedure of this approach, together with the proposed CO2PE! template, is illustrated by means of a case study of a laser cutting process. The CO2PE! methodology aims to provide high-quality LCI data for the machine tool use phase of manufacturing unit processes, to be used in life cycle inventory databases and libraries, as well as to identify potential for environmental improvement based on the in-depth analysis of individual manufacturing unit processes. Two case studies illustrate the applicability of the methodology.

Methodology for systematic analysis and improvement of manufacturing unit process life-cycle inventory (UPLCI)—CO2PE! initiative (cooperative effort on process emissions in manufacturing). Part 1: Methodology description

This report proposes a life-cycle analysis (LCA)-oriented methodology for systematic inventory analysis of the use phase of manufacturing unit processes providing unit process datasets to be used in life-cycle inventory (LCI) databases and libraries. The methodology has been developed in the framework of the CO2PE! collaborative research programme (CO2PE! 2011a) and comprises two approaches with different levels of detail, respectively referred to as the screening approach and the in-depth approach. The screening approach relies on representative, publicly available data and engineering calculations for energy use, material loss, and identification of variables for improvement, while the in-depth approach is subdivided into four modules, including a time study, a power consumption study, a consumables study and an emissions study, in which all relevant process in- and outputs are measured and analysed in detail. The screening approach provides the first insight in the unit process and results in a set of approximate LCI data, which also serve to guide the more detailed and complete in-depth approach leading to more accurate LCI data as well as the identification of potential for energy and resource efficiency improvements of the manufacturing unit process. To ensure optimal reproducibility and applicability, documentation guidelines for data and metadata are included in both approaches. Guidance on definition of functional unit and reference flow as well as on determination of system boundaries specifies the generic goal and scope definition requirements according to ISO 14040 (2006) and ISO 14044 (2006). The proposed methodology aims at ensuring solid foundations for the provision of high-quality LCI data for the use phase of manufacturing unit processes. Envisaged usage encompasses the provision of high-quality data for LCA studies of products using these unit process datasets for the manufacturing processes, as well as the in-depth analysis of individual manufacturing unit processes. In addition, the accruing availability of data for a range of similar machines (same process, different suppliers and machine capacities) will allow the establishment of parametric emission and resource use estimation models for a more streamlined LCA of products including reliable manufacturing process data. Both approaches have already provided useful results in some initial case studies (Kellens et al. 2009; Duflou et al. (Int J Sustain Manufacturing 2:80–98, 2010); Santos et al. (J Clean Prod 19:356–364, 2011); UPLCI 2011; Kellens et al. 2011a) and the use will be illustrated by two case studies in Part 2 of this paper (Kellens et al. 2011b).