Development Framework of an Artificial Intelligence Planner Framework for Bespoke Precast Concrete Production

Vacharapoom Benjaoran1 & Nashwan Dawood2

1PhD Candidate, Centre for Construction Innovation Research, University of Teesside, Middlesbrough, TS1 3BA, UK, +441-642-342494, b.vacharapoom@tees.ac.uk
2Professor, Centre for Construction Innovation Research, University of Teesside, Middlesbrough, TS1 3BA, UK, +441-642-342405, FAX +441-642-342401, n.n.dawood@tees.ac.uk

Abstract

Precast concrete industry is highly involved in construction projects through the supply of bespoke products. It delivers many advantages to the construction industry in terms of saving time, cost, and reducing congestion on construction sites. However, precast manufacturers are facing a substantial problem of long customer lead-time for bespoke concrete products. Most of time and effort is spent on a long production process consisting of product design, production planning, and shop floor manufacturing. Also, variations in the process due to many uncertainties, many parties and human involvements extend buffers of the customer lead-time. Lean construction concepts that are adapted for the unique production system of construction work recognize the above problem as waste and directly aim to eliminate them. Complying with the concepts, the authors have proposed an automatic planning system called artificial intelligence planner (AIP). The AIP retrieves product data from design process for the automatic planning process. In order to develop requirements and specifications of the AIP, this paper concisely describes precast design and production planning processes from a case study of a precast company. Artificial intelligence and flow-shop scheduling techniques that provide development background are reviewed. Also the components of the AIP are described. The AIP is expected to reduce the customer lead-time, assist precast manufacturers to manage changes in product requirements and/or delivery dates; therefore, the construction industry will share the benefits.

Keywords

Precast production, bespoke product, customer lead-time, artificial intelligence, flow-shop scheduling, planning.

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Reference

Benjaoran, V. & Dawood, N. 2003, 'Development Framework of an Artificial Intelligence Planner Framework for Bespoke Precast Concrete Production' In:, 11th Annual Conference of the International Group for Lean Construction. Virginia, USA, 1-.

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