Fazleena Badurdeen

Extending total life-cycle thinking to sustainable supply chain design

Conventional supply chain management (SCM) practices have focused only on three life-cycle stages: pre-manufacturing, manufacturing and use. The fourth stage, post-use, probably the most important from a sustainability perspective, is often addressed on a piece-meal basis, only when such practices deliver economic benefits. This paper introduces a total life-cycle-based approach to sustainable SCM (SSCM) that extends beyond the 3Rs of reduce, reuse and recycle to 6Rs that includes recover, redesign and remanufacture. A new definition for SSCM that adopts the total life-cycle approach and triple bottom-line (TBL) is presented. Two existing supply chain frameworks: supply chain operations reference (SCOR) model and the global supply chain forum (GSCF) framework, are evaluated in the context of SSCM to improve economic growth while ensuring environmental protection and societal well-being. The review finds that neither framework explicitly captures the non-economic aspects of SSCM, but the broader view of the GSCF framework offers much promise.

Integrating lean and other strategies for mass customization manufacturing: a case study

Mass customization (MC) manufacturing requires high flexibility to respond to customer needs in a timely manner. Lean manufacturing principles can be easily applied to situations with low levels of MC. However, as the degree of customization increases and customer involvement occurs earlier in the design and fabrication stages, the direct application of lean principles to maintain flow and low levels of inventory becomes difficult. This paper presents a framework to show how other strategies such as Quick Response manufacturing/POLCA, Theory of Constraints, Flexible/Reconfigurable Manufacturing Systems, etc. can be integrated with lean in MC environments. A case study of boat mass customizer is then used to demonstrate how their operations are transformed by for more efficient MC. Simulation models are used to compare pre- and post-improvement performance.

Product Sustainability Index (ProdSI)

As a result of the rapidly depleting global resources, continuing climate change and increasing environmental pollution, and the associated growth in customer awareness, improving product sustainability has become a global trend. Comprehensive sustainability assessment techniques are needed to assess a products sustainability performance throughout its entire life cycle. This article presents the Product Sustainability Index (ProdSI) methodology and its application. This methodology is metrics based and provides a comprehensive assessment of the overall product sustainability throughout its total life cycle, covering the four life cycle stages: pre‐manufacturing; manufacturing; use; and postuse. In this article, first the fundamentals of sustainable manufacturing and product sustainability assessment (PSA) are presented, followed by a review of existing PSA methodologies. Major product sustainability elements that are used to define product sustainability clusters and individual sustainability metrics are then presented. Finally, the ProdSI methodology for PSA, which follows a hierarchical approach for sustainability metrics identification and overall PSA, is introduced. The application of the methodology is demonstrated in a numerical example of ProdSI evaluation for two generations of a consumer electronics component.

A Framework of Product and Process Metrics for Sustainable Manufacturing

This paper presents a framework for developing comprehensive product and process metrics for sustainable manufacturing, using machined products and machining processes examples, and addressing all three aspects of the triple bottom line – environment, economy and society. The need for developing standardized metrics is discussed for the wider use of these metrics by different manufacturers. The occurrence of similar measurements in some of the metric categories indicates the potential and need for data sharing between product and process metrics. The differences, relationships, and potential interactions between the product and process metrics are discussed from the viewpoint of their applications.

Teaching Lean Manufacturing With Simulations and Games: A Survey and Future Directions

Problem-based learning focuses on small groups using authentic problems as a means to help participants obtain knowledge and problem-solving skills. This approach makes problem-based learning ideal for teaching lean manufacturing, which is driven by a culture of problem solving that values learning as one key output of manufacturing production. Thus, simulations that organize participants in teams for realistic manufacturing production problem solving are widespread as a way to use problem-based learning to teach lean manufacturing. But a critical assessment of existing simulations for lean manufacturing instruction has been lacking. Accordingly, a literature survey is conducted and existing simulations are classified according to their emphasis on lean tools or the overall lean system; the degree of their focus on soft skills, if any; and their area of application, whether academic or industry. Four gaps are found in existing simulation designs: lack of stress on soft skills, a mistaken focus on “linear lean,” misunderstanding of the key role of the facilitator, and lack of realism. Future directions for study and improvement in lean simulation design are suggested.

An analytical hierarchy process‐based tool to evaluate value systems for lean transformations

Purpose – True lean transformation has proved notoriously difficult for non‐Toyota companies. One hypothesis is excessive focus on tools/techniques without building the necessary organizational culture. However, empirical evidence is not available to confirm (or refute) this hypothesis. The complex question of the relationship between an organizations culture and its ability to implement lean is a long‐term effort. As a first step, the purpose of this paper is to offer the results of a survey conducted to discover the relative (in)consistency of lean cultures in terms of values held explicitly.Design/methodology/approach – A survey tool was developed to compare what employees of lean (or attempting to be lean) organizations say explicitly about what their culture values. The Toyota Way, considered by Toyota as guiding its values, was used as the basis to develop the survey which was administered to individuals in several different organizations.Findings – A higher degree of lean implementation in a compa...

Quantitative modeling and analysis of supply chain risks using Bayesian theory

Purpose – Globally expanding supply chains (SCs) have grown in complexity increasing the nature and magnitude of risks companies are exposed to. Effective methods to identify, model and analyze these risks are needed. Risk events often influence each other and rarely act independently. The SC risk management practices currently used are mostly qualitative in nature and are unable to fully capture this interdependent influence of risks. The purpose of this paper is to present a methodology and tool developed for multi-tier SC risk modeling and analysis. Design/methodology/approach – SC risk taxonomy is developed to identify and document all potential risks in SCs and a risk network map that captures the interdependencies between risks is presented. A Bayesian Theory-based approach, that is capable of analyzing the conditional relationships between events, is used to develop the methodology to assess the influence of risks on SC performance Findings – Application of the methodology to an industry case study for validation reveals the usefulness of the Bayesian Theory-based approach and the tool developed. Back propagation to identify root causes and sensitivity of risk events in multi-tier SCs is discussed. Practical implications – SC risk management has grown in significance over the past decade. However, the methods used to model and analyze these risks by practitioners is still limited to basic qualitative approaches that cannot account for the interdependent effect of risk events. The method presented in this paper and the tool developed demonstrates the potential of using Bayesian Belief Networks to comprehensively model and study the effects or SC risks. The taxonomy presented will also be very useful for managers as a reference guide to begin risk identification. Originality/value – The taxonomy developed presents a comprehensive compilation of SC risks at organizational, industry, and external levels. A generic, customizable software tool developed to apply the Bayesian approach permits capturing risks and the influence of their interdependence to quantitatively model and analyze SC risks, which is lacking.

Integrating Sustainable Product and Supply Chain Design: Modeling Issues and Challenges

Promoting sustainability within business operations requires sustainable products, processes, and system, i.e., sustainable supply chains (SSCs). To efficiently reduce environmental and societal impacts of supply chains (SCs) while maintaining continued profitability, it is necessary that the entire SC is designed and managed from a total life-cycle perspective considering coordination between product, process, and SC design. Coordinating product and SC design decisions play a critical role in improving the SSCs performance. The product design determines all its future costs, both in forward and reverse-flow, which in turn depend on the SC configuration such as the number and location of SC partners their capabilities and capacities. Therefore, coordinating sustainable product and SC design decisions requires consideration of all four product life-cycle stages and incorporating a closed-loop flow within the SC. The purpose of this paper is twofold. First, it emphasizes on the need and importance of coordinating product and SC design decisions in SSCs (through illustrative case studies) and the limitations of existing models from a SSC perspective. Second, the paper explains some of the challenges that need to be addressed while developing such holistic integrated models, provides key factors influencing their performance, and thereby proposes a framework to perform this coordination.

A Metrics-Based Methodology for Establishing Product Sustainability Index (ProdSI) for Manufactured Products

The paper presents a new methodology for generating the five-level Product Sustainability Index (ProdSI) based on a set of product sustainability metrics. The evaluation method includes processes of data normalization, weighting and aggregation. Data normalization is applied to convert measured physical data into dimensionless scores that each metric specifies. Weighting factors are assigned and the priority evaluation methodologies are discussed. The normalized data is aggregated to generate a ProdSI score to represent the actual sustainability content in the product. Finally, a demonstration of the methodology is presented with a numerical example.

A multidisciplinary decision support tool for evaluating multiple biorefinery conversion technologies and supply chain performance

Fuels from biomass resources have emerged as a promising alternative to fossil fuel. Widely distributed source locations, varying feedstock, and specific regional conditions make it challenging to develop an optimization model that can be applied to any region to estimate the overall economics of producing these biofuels. The lack of a region specific, flexible optimization model makes it difficult for stakeholders like local policy makers, growers, and investors to make informed decisions about the economic viability and social and environmental impacts of biomass utilization. This novel contribution will illustrate an approach to develop a region specific optimization model which links various aspects of the biofuel supply chain such as feedstock source location, upstream and downstream logistics, as well as thermochemical and biochemical processing. This research shows how various individual optimization models can be combined, resulting in a complete, multivariable economic optimization model for a regional biomass network, paving a pathway for future work to develop an integrated framework for sustainability. The research demonstrated in this contribution illustrates the development of a model that can form the basis of a generalizable decision support tool that can guide investors and policy makers in making critical assessments on a local level in any particular region of interest. As a proof of concept, a portion of the described model will be validated using the Jackson Purchase region of Western Kentucky, USA, which is adjoining many coal fields and has various bio-based feedstocks.