Springer Nature is making SARS-CoV-2 and COVID-19 research free. View research | View latest news | Sign up for updates

A diagnostic model for green productivity assessment of manufacturing processes


Goal, Scope and Background

Green 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.


The 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 Conclusion

The 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 Perspective

Expert 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.

This is a preview of subscription content, log in to check access.


  1. [1]

    APO (2000): Green Productivity in Asia: APO’s Demonstration Projects 1995-1999. Asian Productivity Organization

  2. [2]

    ISO (1997): ISO 14040: Environmental Management - Life Cycle Assessment - Principles and Framework. International Organization for Standardization

  3. [3]

    Besnainou J, Coulon R (1996): Life-Cycle Assessment: A System Analysis. In: Curran MA (ed), Environmental Life-Cycle Assessment. New York: McGraw-Hill

  4. [4]

    SETAC (1993): Guidelines for Life-Cycle Assessment: A Code of Practice. Brussels: Society of Environmental Toxicology and Chemistry

  5. [5]

    Huang YL, Edgar TF (1995): Knowledge-Based Design Approach for the Simultaneous Minimization of Waste Generation and Energy Consumption in a Petroleum Refinery. In: Rossiter, A., (ed), Waste Minimization through Process Design. New York: McGraw-Hill

  6. [6]

    Spengler T, Geldermann J, Hahre S, Sieverdingbeck A, Rentz O (1998): Development of a Multiple Criteria Based Decision Support System for Environmental Assessment of Recycling Measures in the Iron & Steel Making Industry. J Cleaner Prod 6: 37–52

  7. [7]

    Saaty TL (1982): Decision Making for Leaders: The Analytic Hierarchy Process for Decisions in a Complex World. California: Lifetime Learning Publications

  8. [8]

    Seppala J, Basson L, Norris GA (2001): Decision Analysis Frameworks for Life Cycle Impact Assessment. J Ind Ecol 5 (4) 45–68

  9. [9]

    Bohm E, Walz R (1996): Life-Cycle Analysis: A Methodology to Analyse EcologicalConsequences Within A Technology Assessment Study? International Journal of Technology Management, Special Issue on Technology Management 2 (5/6) 554–565

  10. [10]

    Madu CN, Kuei C, Madu IE (2002): A Hierarchic Metric Approach for Integration of Green Issues in Manufacturing: A Paper Recycling Application. J Ind Ecol 64, 261–272

  11. [11]

    Pineda-Henson R, Culaba AB, Mendoza GA (2002): Evaluating Environmental Performance of Pulp and Paper Manufacturing Using the Analytic Hierarchy Process and Life-Cycle Assessment. J Ind Ecol 6(1) 15–28

  12. [12]

    Leffland K, Kaersgaard H, Anderson I (1998): Comparing Environmental Impact Data on Cleaner Technologies: Technical Report No. 1. Copenhagen: European Environment Agency

  13. [13]

    ISO (1999): ISO 14031: Environmental Management - Environmental Performance Evaluation - Guidelines. Geneva: International Organisation for Standardisation

  14. [14]

    Jasch C (2000): Environmental Performance Evaluation and Indicators. J Cleaner Prod 8: 79–88

  15. [15]

    Kuhre WL (1998): ISO 14031: Practical Tools and Techniques for Conducting an Environmental Performance Evaluation. Prentice Hall, New Jersey

Download references

Author information

Correspondence to Ruby Pineda-Henson or Alvin B. Culaba.

Rights and permissions

Reprints and Permissions

About this article

Cite this article

Pineda-Henson, R., Culaba, A.B. A diagnostic model for green productivity assessment of manufacturing processes. Int J LCA 9, 379–386 (2004).

Download citation


  • Analytic hierarchy process
  • diagnostic prototype
  • expert system
  • green productivity
  • life cycle assessment
  • performance indicators
  • semiconductor assembly/packaging