Transformative demands for ERP functionalities: knowledge management in customized manufacturing

Abstract

Customized manufacturing requires completely new technological solutions and long and careful prototype development and testing. The new requirements increase production costs, extend manufacturing time and entail frequent errors in the product quality. So far, knowledge management framework provided by ERP systems still has not responded to the customized needs even though ERP’s provide plenty of innovation solutions for prognosis, trending, etc. Additionally, high uncertainty of customization could be managed better by employing diverse expertise of employees if their knowledge could be empowered together with rigid knowledge about the customized order. The goal of this paper is to determine customized manufacturing demands for functionalities of knowledge management systems that can be incorporated in ERP. The research is based on a case study conducted in an SME type company settled in Lithuania. Extended interviews on different issues, including the decision making system, problem solving, strategic decisions and ERP implementation and use, have been conducted during the last 2 years (from June, 2016 to March, 2018) with company leaders, managers, constructers and production workers. Although, one may expect to accrue experience and improve abilities with every new order, the company is still facing difficulties in coping with uncertainties of incoming orders even after ERP was implemented and launched. In conclusions, customized manufacturing is intensively looking for new knowledge management solutions that meet strictly defined requirements with new ERP functionalities that could be explicit as system based on employee participation and machine learning. The main functionalities could be listed as following: 1.) to make prognostic price estimations for customized and unique orders; 2.) to classify new orders specifying what additional capacities are require to develop the product; 3.) to recognize and accumulate any data that can be stored in the system for future solutions; 4.) to provide guidelines for knowledge management at all stages of knowledge acquisition, transformation and application.