Evaluate the Functionality of the Quality System

Evaluation of module-based quality system functionality in production logistics on a Quality, as a definitive factor in all aspects of any organization guarantees long-term success (Tari, Molina-Azorín & Heras, 2012). One of the main competitive advantages in this regard is the successful implementation of an effective Quality Information System (QIS) (Psomas, Kafetzopoulos & Fotopoulos, 2013; Wahid & Corner, 2009). Since, quality operations can no longer be performed in documents because manual handling of quality data is very error-prone and inefficient, or as individual back office systems, integrated systems provide the desired benefits in an automated manufacturing environment (Law & Tak, 2003). As a relatively new attempt to integrate with manufacturing information systems, QIS improves the efficiency of any application of production logistics information systems as a broader and general perspective view (Anderson, Germany & Crum, 1998; Tak & Hang, 2002). Therefore, applications such as finding the root of quality problems in the product life cycle will be handled efficiently (Ngai, Chau & Chan, 2011). In fact, QIS has to ensure delivery of data of the right quality to the right people at the right time. This in turn will highlight the critical key role of data modeling based on careful business process analysis as the backbone structure of QIS development. In addition, quality data should not be considered as another property of manufacturing objects such as lots or items or groups of items in the manufacture of control information systems (Khabbazi, Ismail, Ismail, Mousavi & Mirsanei, 2011). Thus, the need to consider the quality system as another operational module in the design and development of modular systems for production logistics is dramatically seen as critical. As part of a larger effort to undertake extensive modeling of module-based inbound and outbound logistics systems at the supply chain level, this paper complements the development of quality system data modeling {see: #813} by emphasizing business process modeling as an additional step. This is followed by prototype implementation and evaluation of data model functionality focusing on quality operations at the highest domain level. Explanatory techniques used in business processes and data modeling provide a broad descriptive picture of the structure and behavior of the system. The proposed analytical BPM and object-oriented data model are considered referential for further development at a lower abstract level. They are used as a roadmap for developing a prototype database of actual design steps to evaluate the functionality requirements of the quality system. Quality system requirements are highlighted and solution functionality based on identified requirements is evaluated through data queries providing real-time control capabilities. The modular based design is another advantage of the proposed system which proves its integration capability with other back-office systems in SMEs. The reminder of this paper is built in four main flowing sections. This introduction is followed by a quality system and requirements, a description of the methodology explaining the procedures adopted for model development and functionality evaluation, model development, and functionality evaluation. The conclusion is presented in the last section followed by a list of references.