Module property verification : A method to plan and perform quality verifications in modular architectures

Modular product architectures have generated numerous benefits for companies in terms of cost, lead-time and quality. The defined interfaces and the module’s properties decrease the effort to develop new product variants, and provide an opportunity to perform parallel tasks in design, manufacturing and assembly. The background of this thesis is that companies perform verifications (tests, inspections and controls) of products late, when most of the parts have been assembled. This extends the lead-time to delivery and ruins benefits from a modular product architecture; specifically when the verifications are extensive and the frequency of detected defects is high. Due to the number of product variants obtained from the modular product architecture, verifications must handle a wide range of equipment, instructions and goal values to ensure that high quality products can be delivered. As a result, the total benefits from a modular product architecture are difficult to achieve. This thesis describes a method for planning and performing verifications within a modular product architecture. The method supports companies by utilizing the defined modules for verifications already at module level, so called MPV (Module Property Verification). With MPV, defects are detected at an earlier point, compared to verification of a complete product, and the number of verifications is decreased. The MPV method is built up of three phases. In Phase A, candidate modules are evaluated on the basis of costs and lead-time of the verifications and the repair of defects. An MPV-index is obtained which quantifies the module and indicates if the module should be verified at product level or by MPV. In Phase B, the interface interaction between the modules is evaluated, as well as the distribution of properties among the modules. The purpose is to evaluate the extent to which supplementary verifications at product level is needed. Phase C supports a selection of the final verification strategy. The cost and lead-time for the supplementary verifications are considered together with the results from Phase A and B. The MPV method is based on a set of qualitative and quantitative measures and tools which provide an overview and support the achievement of cost and time efficient company specific verifications. A practical application in industry shows how the MPV method can be used, and the subsequent benefits

Praktiska effekter av begreppsförvirring för en databas konceptuella design : En fallstudie om databas- och begreppsmodellering

Company X develops a laboratory information system (LIS) called System Y. The informationsystem has a two-tier database architecture consisting of a production database and a historicaldatabase. A database constitutes the backbone of a IS, which makes the design of the databasevery important. A poorly designed database can cause major problems within an organization.The two databases in System Y are poorly modeled, particularly the historical database. Thecause of the poor modeling was unclear concepts. The unclear concepts have remained in thedatabase and in the company organization and caused a general confusion of concepts. The splitdatabase architecture itself has evolved into a bottleneck and is the cause of many problemsduring the development of System Y.Company X investigates the possibility of integrating the historical database with the productiondatabase. The goal of our thesis is to conduct a consequence analysis of such integration andwhat the effects would be on System Y, and to create a new design for the integrated database.We will also examine and describe the practical effects of confusion of concepts for a databaseconceptual design.To achieve the goal of the thesis, five different method steps have been performed: a preliminarystudy of the organization, a change analysis, a consequence analysis and an investigation of theconceptual design of the database. These method steps have helped identify changes necessaryfor the organization, a new design proposal for an integrated database, the impact of theproposed design and a number of effects of confusion for the database.