This essay has been submitted by a student. This is not an example of the work written by our professional essay writers.
This paper looks at software quality management in regards to the manufacturing sector and how methods, tools, models and the integration of various languages are used to aim to overcome the complexity of modern manufacturing management software systems. The various management systems are outlined, followed by the various tools split into four groups namely diagnostic reference tools, information tools, dynamic simulation tools and integrated tools. The report finishes by evaluating these tools and pointing out the problems that need to be overcome in producing quality software.
The methods and tools for software quality is a wide ranging topic and for this reason this report will view it from the perspective of manufacturing systems. There are many manufacturing management tools such as Just in Time (JIT), Total Quality Management (TQM), Activity Based Costing (ABC) and Lean Manufacturing to name a few. All of these require quality software to be able to give proper manufacturing process instructions, gather relevant data, monitor the systems, analyse data and give relevant feedback for management to carry out strategic planning. This is all at the same time when manufacturers are attempting to drive down costs while identifying and maintaining customer value, relying on reliable software for this. An overview of various methods and tools for software quality management will be presented, followed by an evaluation and the limitations of the various models will be outlined.
2.0 Software Quality Management and Integration with Manufacturing Process
Software quality is very important and relies on continual improvement to increase the flexibility and deliverability to meet the customer requirements. There are many cases where software design is used in the manufacturing sector to improve performance and create efficiencies. These include the following items:
Recognising cost, resource and capacity waste
Disorder recognition in regards to control flow, material and information
Performance improvement through redesigning the manufacturing process
Enterprise Resource Planning (ERP)
Business Process Reengineering (BPR)
Product Data Management (PDM)
Manufacturing Execution Systems (MES)
Just In Time Inventory Management strategies
Total Quality Management software
ABC Cost Accounting software
Quality assurance software for ISO9000 and Iso 14000.
Below is set out Figure 1 which outlines the various parts of a manufacturing analysis process and an overall view of the areas that are impacted. This starts with the initial phase where the whole system is analysed using more traditional systems engineering and engineering methods. By carrying out this initial phase then an evaluation of the strong and weak aspects can be pointed to. There is also the opportunity to identify the activities that need improvement to reach the highest level of performance. Decisions are made in the second phase which enable the selection of the best improvement techniques for the specific requirements and the situation that has arisen for the manufacturing system. The last phase requires the measurement of the output to consider future actions based on the results and feedback systems. This feedback system is part of the cyclical process of reaching excellence through continuous improvements and modifications. To maximise the effectiveness of the cycle process the KPIs need to be identified and apply the activity based costing management techniques. Rather than using ratios and summary data at each of these three levels, it is best to integrate them so that improvements are made greater then would have been achieved if the standards and tools were used separately. The whole is greater than its parts. Previous research into the field of software quality management tools in the manufacturing sector have included both case studies and theory building research (Felix and Bing, 2001). In these studies they are looking at various performance indicators such as improvements in productivity, cost, flexibility, quality and lead team to achieve correct solutions for a specified system requirement. There are problems in this approach which is why in practice in the manufacturing sector, companies do not implement these systems. The question is why. The next section sets out the various techniques that can be used in a software quality management development.
Figure 1: Methods Tools and Techniques in Manufacturing Systems.
3.0 Software Quality Management Techniques
There are several tools and metrics that can be used when moving through the various stages as shown in Figure 1. The range of tools to be able to group the various techniques can be set into four sections. This allows a step by step analysis of these tools. These sub sections are diagnostic reference tools, information tools, dynamic simulation tools and integrated tools.
3.1 Diagnostic Reference Tools
The implementation phase of new manufacturing software to aid in the management of a business, relies on the various methodologies that allow an overview of the companies situation in relation to the optimum outcome. These manufacturing model outcomes include Just In Time, Total Quality Management, Lean Manufacturing and Activity Based Costing to name just a few. To be able to gather the appropriate information to develop the best software then input from many stakeholders is appropriate using such instruments as on line questionnaires, in person interviews and surveys to be able to gain an understanding of all involved. The line of enquiry would establish what is the current situation, where the management would like the software systems to go and the gaps and difficulties that need to be overcome during the process. Benchmarking the current situation and the final outcomes against industry standards allows the project to be evaluated and determine if it is practical (Aqualino and Chase, 1991). A questionnaire has been developed to cover the various contingencies and been adapted since 1991 by manufacturing companies and consultancy firms servicing these groups. The benefit of using the Aqualino and Chase (1991) is that it groups the main aspects of a manufacturing system together into the required categories so they can be evaluated against the industry benchmark and areas of clarification and enhancement can be identified. Part of the process is to look at such aspects as the manufactures product structure. The various flows of materials and labour inputs, the integration of the manufacturing operations with the rest of the company, planning and leading into other subsequent systems such as the sales and the distribution channel systems.
The methods for ensuring software quality is attained along with the manufacturing process was outlined by Vollmann, Dixon and Nannu (1989) where they outlined diagnostic methods and tools to be able to analyse the measurement and outputs of a manufacturing plant. As with the previous work mentioned , this questionnaire aims to measure the key performance indicators in a system development and show where there is variance from the benchmark standards. The benefit in using such a tool is that the development is able to ascertain if it is reaching the optimal level it can from the software development, against what has already been done. This is useful where the development is attempting to meet standards for a manufacturing process that has been carried out before. The problem arises in these innovative times where the manufacturing of new specialised products is being attempted where the meeting of existing standards may retard the software development not allowing it to go beyond what has been done before.
In the case of achieving a Lean Manufacturing system, which is preferred in current manufacturing modelling, Jackson (1996) developed a survey instrument that takes the results and compares the answers to an existing manufacturing model standard and then gives the software development corrections to move towards a lean manufacturing system. In the advancement of manufacturing systems the lean manufacturing production was recognised in the 1990s, as a production system that looks at the cost of resources for the outcome including the value for the end customer, and may be seen as wasteful and able to be cut out of the process. The idea is to look at the value added to the customer by the manufacturing process and if this value is something a customer is willing to pay for. The idea of lean manufacturing is that value is retained with passing on lower costs (Holweg, 2007). This system came from Toyota and the Toyota Seven Wastes process that aims to increase customer value while still identifying efficiencies in the manufacturing system, which has helped Toyota being propelled to the number one car manufacturing in the world. To help achieve this there is a close tie in between the identification of waste and the software that is used to identify, record waste and identify possible solution to waste problems. The Lean Manufacturing method has been further assessed by Trischler (1996) with a model that carries out an analysis of the manufacturing process to identify activities that add no value to the manufacturing. This model goes further in that it offers a way of improving the process against a diagnostic reference.
Another diagnostic reference tool was identified by Seidel (1998) who showed a methodology which looked at evaluating improvement in productivity in the manufacturing job costing analysis. This method looked at eight areas of purchases, engineering, plant distribution, planning, manufacturing, programming, customers and design. There is a link between the various eight categories through a matrix system of comparing the productivity of one category with the identification of problems in another. This enables the software development project to quantify the areas of improvement within the eight categories by looking at their lower performance. Another diagnostic reference model focuses on a series of flags as a way of indicating variations against an integrated model as the process sis being carried out. The idea being to make available strategic indicators for the implementation of a Total Quality Management (TQM) system. From this work came the European development of the ESPRIT TQM-Til which is a web tool to permit the flagging of strategic indicators in OLAP databases. These highly developed web tools are the latest development in diagnostic reference methods.
3.2 Information Tools
These are viewed as the most important technique for the software quality in manufacturing system s. This has led to various project modelling methodologies being used for knowledge management as they capture an understanding of, reengineering, evaluation and optimisation of the manufacturing process. Figure 2 outlines the history of the various modelling techniques over the years and out of this history has come many process information tools.
Figure 2: Modelling History
From these the IDEF range of information tools and in particular IDEF3 and the most widely used and simplest. The definition of IDEF is ââ‚¬Å“a system is a set of activities that takes certain inputs and, using some mechanism, subject to certain of controls, transforms those inputs into outputs. Such objects can be used to model relationships among various activitiesââ‚¬ (Mayer and Menzel, 1995). The reason IDEF is so widely used is it allows the analysis of very complex processes where there are many levels of information regarding each activity and allows the analysis to go ahead to comprehend the system. In looking at the use of IDEF, there are many studies that have looked at the use of this with manufacturing software modelling including design techniques (Colquhoun, Gamble and Braines, 1989), concurrent engineering (Howard and Lewis, 2003) and Enterprise Resource Planning (Kwon and Lee, 2001). There has also been research into the use of IDEF in small and medium size enterprises. What this variety in research shows is that there is flexibility in the use of IDEF0 and IDEF3 information tools to allow the analysis of manufacturing systems at many levels.
As such a simple information tool, IDEF does have its limitations as a it is a descriptive basis for the graphical and text of data, information and functions within the development. It is mainly used to document and validate a process as it s a fixed and static tool. This is a problem in defining and analysing a flexible and dynamic process with its parts ever changing and where the dimension of time is not taken into consideration. This of course is vital in a manufacturing process based on time efficiencies and identifying time wastage. Another limitation of the IDEF tool is that it incorporates a level of abstraction with assumption of various processes being made to take into account the quantitative information to allow for the process variables that are being identified (Zakarian and Kusiak, 2000). These limitations flow onto the suggested improvements of IDEF information tools also having their own limitations.
Given the limitations of IDEF, there have been attempts to overcome these problems. These include the use of Fuzzy Logic and Petri Nets with IDEF and IDEF3. Ma, Zhang, and Ma (2002) have looked at a model to add onto the IDEF1X tool which allows the representation of fuzzy logic. For both of these the relevance to the end user is difficult due to the complexity of the implementation. Another approach has been the use of UML as an addition to the information tools to allow for the drawbacks. UML is a modelling language to allow computer executable tools that encode software programming and also allows process modelling. There is a similarity between the objects used in IDEF and UML which leads to an easier integration of the two systems( Kim,Weston, Hodgson, and Lee, 2003). The use of these two tools together also leads to the linking of descriptions within the manufacturing process and the behaviours of the manufacturing machinery, suppliers, workers and the output product. UML is also used to evaluate the control processes within a simulation model. By carrying out simulations with varying scenarios of inputs and behaviours, this leads to opportunities in improving the evaluation of the process outside the real manufacturing to make adjustments to the real world. This is covered in the next section of the report.
3.3 Dynamic Simulation Tools
Simulation tools have been used since the early years of modelling in the 1960s. This has been used to gain a comprehension of the flows of manufacturing processes. Since the 1990s with the advances in computing power and the flexibility of software languages, there has been a greater use of simulation to optimise manufacturing, logistics and warehousing efficiencies. The benefit of this is configuring the use of limited resources to maximise their efficient use or establish of other combinations of resources can reach a better outcome (Tillal and Ray, 2001). The simulation tools are in best use where they are applied to specific identified manufacturing problems, such as planning, bottlenecks, waste and scheduling (Williams & Naraya, 1997). Other than manufacturing flow problems, there is also the application of simulation to specific manufacturing management techniques including, JIT system design, business process reengineering and TQM (Irani, Hlupic, Baldwin, & Love, 2000). The use of these simulation modelling tools allows the reduction in programming time as well as gaining an understanding of for the software will interact with the manufacturing process and thus improve the quality management of the software. This does rely on clear specifications to maximise the use of the simulation to the real world situation. It is the combination of the use of simulation tools and other software methods and techniques that allows the maximisation of the quality of software, reducing time and gaining a closer fit to actual real processes.
3.4 Integrated Tools
There are several techniques which use the combination of a simulation tool and other representative tools to gain a best fit between the simulation and the real specifications. The paper by Rojas and Martinez (1998) was able to develop a model of the capture, description and analysis of the relevant behaviour to generate code for a simulation model. This is based on Role Activity Diagram (RAD) technique. This also requires the use of qualitative and quantitative data to assist through the integration of the various software components including with the web and company databases by using Open Database Connectivity (ODBC) extensible markup language (XML) and comma separated version (CSV) data formats. There is a rich array of information gathered to compliment the simulation including the objectives and decisions that are required to reach the goals of the manufacturing system. This is able to be achieved using the Witness simulation tool which maps the interaction between the various elements of the model. These elements may include the activities, relations and decisions and how they play out with the simulator which includes manufacturing machinery, buffers and outputs. Other techniques combine three different models to achieve this best fit goal (Doumeingts,Vallespir,&Chen, 1995). This method combines GRAI to model the decision process, MERISE to model the information process and IDEF0 to model the physical process. By integrating all three models, with the use of a graphical editor to monitor the dynamic parts of the manufacturing process a better outcome is achieved. A further technique is the combining of Data Flow Diagrams (DFDs) and GRAI Grids to create a manufacturing model (Carrie and MacIntosh, 1997). The limitation of this technique is that it does not consider the dynamic aspects of the manufacturing process.
The use of an interface tool to sit over the top of the various models has also been used by Al-Ahmari & Ridway (1999) to combine three techniques of GRAI grid, IDEF0 and SIMAN. The interface has the advantage in that it allows data exchange and user interface with the actual activities to be carried out and the simulation model. This technique also has the advantage that it is able to accommodate dynamic processes. Kang, Kim, and Park (1998) use an ââ‚¬Å“integrated modelling framework for manufacturing systems named IMF-Mââ‚¬ which is able to combine the physical process and the simulation control information at the same time involving the resources, materials, information objects, material flows and processes all the same time. Zakarian andKusiak (2001) developed an integrated framework based on IDEF techniques, stream analysis approach and dynamic simulation. This method is oriented to performing the analysis and reengineering of processes and evaluating the impact of changes. The authors propose modifications to the IDEF3 model. Each activity box is divided into two sections with a phrase describing the activity and an expression that describes the mathematical relationship of the output, input and control elements. This representation is used to formulate a dynamic simulation with DYNAMO modelling language representing a set of linked differential equations describing a closed loop feedback system. This method extends the IDEF3 methodology by including quantitative information.
4.0 Software Evaluation
Now that the various techniques have been set out, following is an evaluation of these software quality management techniques.
Due to the variety of approaches and the various techniques that are being used, there is a problem in reaching a standard for the analysis of these techniques. This is due to the variability of the tools on offer for the software systems and various objectives. This is a function of the complexity of the manufacturing today with so many management techniques as set out before and the use of supply chain management which requires the integration of the manufacturing up and down the supply chain. To gain efficiencies and drive down costs, many products that traditional would not have been used in a manufacturing environment, due to modern automated tooling and systems are able to be manufactures where they would have been done by hand in the past. This can be seen in the use of automated lathing of metal work. Where there was one a labour intensive process, there is now a high quality, low cost and high volumes due to the integration of automation and sophisticated mapping software.
What is the impact on strategic decisions. Where there is a diagnoses tool there is also the need for the reference system to help with the planning and strategic decision of the management. Reference systems have a draw back in that they may not meet the needs of that particular company. BPR is able to be used for knowledge management and creation of value for the consumer. However there are gaps in the information it provides to be able to make future strategic decisions in making adjustment to the manufacturing process based on external contingencies. All aspects that need to be considered for strategic planning.
Level of analysis. A limitation of manufacturing analysis is that gives an adequate picture of the current and historic processes. As outlined before some tools such as the IDEF are static and are not able to cater for flexibility. Data is gathered on past performance without allowing for various scenarios to be considered. There is also the issue of human re skilling and other implementation costs that are not taken into consideration. Other than qualitative modifications, there is a need for quantitative information to be evaluated in the model, such as quality, cost, efficiency, and the cycle time. Otherwise there is an inability to gain the necessary level of quality evaluation of the software management as the true effect of problems are not clarified (Busby, 1992).
Analysis and modelling tool interfaces: The software tools outlines mainly use a graphical object including activities and flows to symbolise the functioning of the system. There is a break down where the tools are not linked with the systems due to the dynamic nature of the manufacturing process and the decision support systems (DSS) . Interpretation of the model diagrams are difficult for the software tools which then requires another layer of interpretative tools, leading to greater complexity and difficulties in maintaining software quality.
Value Added Process: To be able to calculate the value added to the consumers from a product this has been established through supply chain evaluation. This is more difficult in manufacturing engineering. There are so many hidden costs and opportunities for waste that are not easily identified by the consumer, and seen as a given that the value add is difficult to quantify. These inputs include cycle times, over production, waste, transport and warehousing costs. Given these are currently at various levels, each company needs to evaluate their actual levels and where value add in the manufacturing can be reached.
Software Tools Identifying Manufacturing Non Quality Costs: General inputs are able to given a particular costs as paid to suppliers, machine time or wages to workers. It is more difficult to quantify non tangible costs such as waste, reprocessing, quality control and inspections. This is being overcome with the use of ABC and ABM costing software and its application to the manufacturing process (Gupta, Stahl and Whinston, 1997).
Lack of use and research into SMEs: SME manufacturing firms are using traditional software tools based on method engineering (Vernadat, 2002). The benefits of enterprise modelling are usually over looked and seen as too costly or intricate to implement in their manufacturing software systems. Vernadat (2002) outlines other inhibitors to implementing these enterprise manufacturing systems as time to implement, high cost, complexity and the skills of management and software developers to produce and manage such systems.
In conclusion, this report has outlines a thorough look into the methods, techniques and tools that can be implemented to analyse manufacturing software quality and appropriate use for management purposes. When quality software is used meeting company specifications, it is able to cope with the whole process, including producing metric dashboards which allows the management to make accurate decisions not only on the current manufacturing process, but also future strategic decisions. The four sub sections of software tools are assessed with an integrated solution for manufacturing software outlined. As outlined in figure one, there is still a need for the tools in the software development process to meet customer specifications and mainly for dynamic simulation models to maximise customer value from the manufacturing process.