Improving customer delivery performance and job scheduling at a manufacturing SME

Small and medium-sized enterprises (SME’s) need to adopt effective supply chain management practices to deliver reliable performance. Customer delivery performance (CDP) is a commonly used key performance indicator to measure how effectively customer’s promised delivery dates are met. Achieving a go...

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Bibliographic Details
Main Author: Bahety, Dhanraj
Other Authors: Rajesh Piplani
Format: Final Year Project
Language:English
Published: 2017
Subjects:
Online Access:http://hdl.handle.net/10356/72001
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Institution: Nanyang Technological University
Language: English
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Summary:Small and medium-sized enterprises (SME’s) need to adopt effective supply chain management practices to deliver reliable performance. Customer delivery performance (CDP) is a commonly used key performance indicator to measure how effectively customer’s promised delivery dates are met. Achieving a good CDP requires an effective capable-to-promise (CTP) system for promising and then meeting those delivery dates. Manufacturing processes with as multiple production stages in series, each with multiple machines, can be modelled as flexible flow shops. It is common for growing SME’s to have machines with different constraints and capacities, to perform the same operation, installed over time as the company expands. This Final Year Project aims to develop a CTP and job scheduling system to improve the CDP of an SME. Dinman Polypacks Pvt. Ltd. is the focus of this project has provided the information and data used in the development of the algorithms developed. With appropriate changes, the system and algorithms can be applied to any company with a similar manufacturing environment. A job scheduling system developed for their bottleneck manufacturing stage promises dispatch dates after considering current capacity commitments and availability of resources and components/raw materials. It prioritizes the company’s orders, schedules them accordingly, and then ensures that the promised dispatch dates are met. The algorithm for order acceptance first computes the materials required for the order and assigns inventory accordingly, or takes appropriate lead times into account. The algorithms also consider wait times before the bottleneck processes, lead times, and other process times to arrive at a suitable dispatch date. With some customization to reflect the operating conditions and manufacturing processes of the target company, the fundamental principles and logic used in the development of the system would be applicable to any enterprise interested in improving their customer delivery performance and job scheduling.