Alvin B. Culaba

A methodology for the life cycle and sustainability analysis of manufacturing processes

Abstract Life cycle assessment is emerging as a powerful tool in the evaluation of the environmental impact of manufacturing processes. This paper describes a general methodology for the life cycle analysis of manufacturing processes taking into account the flexibility and decision-making potential of knowledge base systems. Emphasis is placed on on-site waste minimisation and associated sustainability characteristics in relation to environmental impact assessment and process improvement. The ensuing software model is applied with some success to an initial study of pulp and paper manufacture.

Evaluating Environmental Performance of Pulp and Paper Manufacturing Using the Analytic Hierarchy Process and Life‐Cycle Assessment

Summary This article addresses the need for a structured and compre-hensive methodology for assessing the environmental perfor-mance of manufacturing processes. The analytic hierarchy pro-cess (AHP) is used as the basic framework for analyzing environmental impacts and improvement options following a streamlined life-cycle assessment (LCA) approach that is fo-cused on the manufacturing operation. The multicriteria de-cision analysis approach of the AHP is consistent with the LCA concept because the environmental factors can be hierarchi-cally structured into impacts and improvement options. Its po-tential as a valuation tool for impact and improvement assess-ment addresses both qualitative and quantitative issues in environmental decision making. Through application to a pulp and paper manufacturing case study, the viability of the AHP for evaluating environmen-tal impacts and prioritizing process improvement options rela-tive to these impacts is demonstrated. AHP was used to pro-vide a quantitative tool for the design of a set of weighting factors for impact and improvement analyses.

Fuzzy optimization of topologically constrained eco-industrial resource conservation networks with incomplete information

It is possible to minimize industrial resource consumption by establishing eco-industrial resource conservation networks (RCN) between different plants. The establishment of these networks requires the satisfaction of quality criteria for material properties deemed significant by an industry. It also necessitates cooperation among the different firms based on the satisfaction of individual cost or resource consumption goals. Furthermore, there may be varying degrees of incomplete information regarding the process data of the participating plants. Eco-industrial RCNs may also be topologically constrained with respect to the number of links connecting different plants. These design aspects are incorporated in the optimization model through fuzzy mixed integer linear programming (FMILP) or fuzzy mixed integer non-linear programming (FMINLP). Case studies from literature involving water integration and hydrogen recovery are used to illustrate the methodology. The model is able to identify the topologically constrained network that achieves the highest level of overall satisfaction among participating plants.

Fuzzy mixed-integer linear programming model for optimizing a multi-functional bioenergy system with biochar production for negative carbon emissions

A multi-functional bioenergy system is an efficient way for producing multiple energy products from biomass, which results in near-zero carbon emissions. To achieve net negative carbon emissions, biochar production as carbon sequestration can be integrated in the system. A fuzzy mixed-integer linear programming model is developed to simultaneously design and optimize a multi-functional bioenergy system given multiple product demands, carbon footprint, and economic performance constraints. Case studies are presented involving multi-functional bioenergy systems with biochar production for carbon sequestration. The results show that net negative carbon footprint can be achieved in such systems.

POLCAGE 1.0—a possibilistic life-cycle assessment model for evaluating alternative transportation fuels

Abstract A composite software model for the comparative life-cycle assessment (LCA) of 10 different fuel options for the Philippine automotive transport sector was developed. It is based on the GREET fuel-cycle inventory model developed by the Argonne National Laboratory for the United States Department of Energy. GREET 1.5a is linked to an impact assessment submodel using the Danish environmental design of industrial products (EDIP) method. This combined inventory–impact assessment model is enhanced further with possibilistic uncertainty propagation (PUP) and possibilistic compromise programming (PCP) features that allow the 10 alternatives to be ranked in the presence of multiple criteria and uncertain data. Sensitivity and scenario analysis can also be performed within the composite model. Some current and anticipated Philippine conditions, including electricity generation mix, are incorporated in the prototype’s built-in database. The software model, designated as POLCAGE 1.0 (possibilistic LCA using GREET and EDIP), is coded in Microsoft Excel and Visual Basic. The model’s capabilities and features are demonstrated using a case study based on its default scenario.

A diagnostic model for green productivity assessment of manufacturing processes

Goal, Scope and BackgroundGreen Productivity (GP) is a new paradigm in sustainable manufacturing where resource conservation and waste minimization constitute the strategy in simultaneously enhancing environmental performance and productivity. This productivity approach to the sustainability of industries requires the adoption of clean production technology and the development of appropriate indicators and instruments to measure environmental performance in a continuous improvement strategy that focuses on the manufacturing stage of the product life cycle. The analysis may be expanded to include the entire life cycle with increasing details on impacts, improvement strategies and indicators.MethodsThe study proposes a methodology for GP assessment that integrates the essential components of life cycle assessment (LCA) and multicriteria decision analysis specifically the analytic hierarchy process (AHP). LCA provides a systematic and holistic perspective for GP analysis that spans inventory, impact and improvement assessment. The AHP is utilized as a decision framework and valuation tool for impact and improvement assessment to come up with priority weights. Indicators are derived and measured from a streamlined LCA focused on a number of parameters within the gate-to-gate analysis to demonstrate the GP concept in relation to resource utilization and waste minimization. An input-output approach using a suitable material balance in a scenario analysis provides the basis of GP performance measurement.Results and ConclusionThe diagnostic model is applied on a semiconductor assembly/packaging operation. From the streamlined life cycle inventory, impact factors were derived for water resource depletion (WRD), energy resource depletion (ERD), human toxicity-air (HTA), human toxicity-land (HTL), human toxicity-water (HTW), aquatic ecotoxicity (ETA) and terrestrial ecotoxicity (ETT). Valuation of impact factors using the AHP showed the high significance of ETT, HTL, WRD and ERD. This especially reflects the impact of the industry on the solid waste problem as a result of emissions to land associated with human toxicity and ecotoxicity effects and the intensive use of water and energy resources. Using scenario analysis, the effect of implementing a process-based improvement technique on a product-specific operation was determined and the highest values in GP are for energy utilization, water utilization and terrestrial ecotoxicity.Recommendation and PerspectiveExpert system technology was explored in developing a diagnostic prototype that emulates how human experts diagnose green productivity of manufacturing processes. The aim was to investigate how such a diagnosis could be performed in an intelligent fashion that it is also easily accessible as a decision support for industries. The expert system model will provide flexibility in testing the relationships of environmental performance and productivity parameters as well as in preserving and disseminating valuable human expertise in GP program implementation. This is a continuing research effort that is building the knowledge base for GP assessment. It will include case studies over a wider range or level of detail regarding the impacts and improvement techniques and the other stages of the product life cycle.

Simultaneous carbon footprint allocation and design of trigeneration plants using fuzzy fractional programming

Trigeneration systems offer an inherently efficient, low-carbon approach to producing useful energy streams. Due to multiple products from a trigeneration system, the challenge of allocating carbon footprint to each energy stream arises, particularly if the streams are sold to different customers. A fuzzy fractional programming model is proposed to design a trigeneration system, taking such allocation into account. The model allows for solving for a configuration that gives the minimum carbon footprint for each energy stream, given a range of values for demand for each product in a trigeneration system. The final design must meet a specified energy output requirement, while satisfying fuzzy carbon footprint limits for all products. The methodology is illustrated using hypothetical but realistic case studies. Sensitivity analysis was carried out to show the effects of changing the system carbon footprint limits.

Optimizing and Characterizing Geopolymers from Ternary Blend of Philippine Coal Fly Ash, Coal Bottom Ash and Rice Hull Ash

Geopolymers are inorganic polymers formed from the alkaline activation of amorphous alumino-silicate materials resulting in a three-dimensional polymeric network. As a class of materials, it is seen to have the potential of replacing ordinary Portland cement (OPC), which for more than a hundred years has been the binder of choice for structural and building applications. Geopolymers have emerged as a sustainable option vis-à-vis OPC for three reasons: (1) their technical properties are comparable if not better; (2) they can be produced from industrial wastes; and (3) within reasonable constraints, their production requires less energy and emits significantly less CO2. In the Philippines, the use of coal ash, as the alumina- and silica- rich geopolymer precursor, is being considered as one of the options for sustainable management of coal ash generation from coal-fired power plants. However, most geopolymer mixes (and the prevalent blended OPC) use only coal fly ash. The coal bottom ash, having very few applications, remains relegated to dumpsites. Rice hull ash, from biomass-fired plants, is another silica-rich geopolymer precursor material from another significantly produced waste in the country with only minimal utilization. In this study, geopolymer samples were formed from the mixture of coal ash, using both coal fly ash (CFA) and coal bottom ash (CBA), and rice hull ash (RHA). The raw materials used for the geopolymerization process were characterized using X-ray fluorescence spectroscopy (XRF) for elemental and X-ray diffraction (XRD) for mineralogical composition. The raw materials’ thermal stability and loss on ignition (LOI) were determined using thermogravimetric analysis (TGA) and reactivity via dissolution tests and inductively-coupled plasma mass spectrometry (ICP) analysis. The mechanical, thermal and microstructural properties of the geopolymers formed were analyzed using compression tests, Fourier transform infra-red spectroscopy (FTIR), scanning electron microscopy (SEM) and thermogravimetric analysis (TGA). Using a Scheffé-based mixture design, targeting applications with low thermal conductivity, light weight and moderate strength and allowing for a maximum of five percent by mass of rice hull ash in consideration of the waste utilization of all three components, it has been determined that an 85-10-5 by weight ratio of CFA-CBA-RHA activated with 80-20 by mass ratio of 12 M NaOH and sodium silicate (55% H2O, modulus = 3) produced geopolymers with a compressive strength of 18.5 MPa, a volumetric weight of 1660 kg/m3 and a thermal conductivity of 0.457 W/m-°C at 28-day curing when pre-cured at 80 °C for 24 h. For this study, the estimates of embodied energy and CO2 were all below 1.7 MJ/kg and 0.12 kg CO2/kg, respectively.

An analysis of the healthcare informatics and systems in Southeast Asia: a current perspective from seven countries

This paper presents an overview of the healthcare systems in Southeast Asia, with a focus on the healthcare informatics development and deployment in seven countries, namely, Singapore, Cambodia, Malaysia, Thailand, Laos, the Philippines and Vietnam. Brief geographic and demographic information is provided for each country, followed by a historical review of the national strategies for healthcare informatics development. An analysis of the state-of-the-art healthcare infrastructure is also given, along with a critical appraisal of national healthcare provisions.

Multi-Regional Multi-Objective Optimization of an Algal Biofuel Polygeneration Supply Chain With Fuzzy Mathematical Programming

A polygeneration approach is proposed to improve the economic viability of algal biofuel production through simultaneous production of co-products (i.e. electricity, heat, and other biochemicals). A multi-regional polygeneration supply chain consists of various array of processing plants in producing multiple bioenergy products given spatial constraints of each plant found in different regions. The inherent complexity of the polygeneration compounds the difficulty of designing the composite network of processing plants in multi-regions. Optimizing the design flow of the polygeneration supply chain considers multiple objectives, such as satisfying product demand, maximizing economic performance, and minimizing environmental footprint. In addition, the optimal strategic capacity design of the supply and distribution of biodiesel across multi-regions are considered. This study uses a fuzzy mathematical programming model to generate an optimized design of the polygeneration supply chain while satisfying all objectives. The developed model is demonstrated using a modified industrial case study comparing two cultivation alternatives. Results showed that all fuzzy multi-objective goals are satisfied and the flat-plate photobioreactor is the preferred cultivation system in terms of environmental footprints and economic performance.Copyright