CHAPTER THREE RAMP-UP PERFORMANCE
An evaluation of ramp-up performance can only be performed based on a suit-able capacity system. According to Beamon (1999), a performance measure or a set of performance measures is normally used to determine the effectiveness as well as efficiency of an active system and to evaluate competing substitute systems. The addition of four characteristics is very important for the establish-ment of such a system. These characteristics are:
Inclusiveness: Which is a measure of every relevant
Universality: Which allows for assessment under different operating con-ditions
Measurability: The necessary data is measurable
Consistency: The measures are regular with the organisational goals
To achieve these goals, most of the established performance measurement systems consist of a set of performance measures and indicators. Browne et al (1997) defined performance measure as “a description of something that can be openly and directly measured”. However, a performance indicator could be de-fined as a description of something that is premeditated from performance measures. A performance measurement system is a full set of performance measures and indicators to achieve completeness. Only efficient and manage-ment process can assure production ramp-up through sustaining productivity as well as efficiency and quality in the production or manufacturing process (Schmidt et al, 2009). The model asserts that the performance of an organisa-tional system is a complex interrelationship between seven performance stan-dards that include profitability, innovation, quality of work life, productivity, qual-ity, efficiency as well as effectiveness. However, the most accepted model has been the balanced scorecard planned by Kaplan and Norton (1996), a concept that integrates and identifies four various groups of performance such as innovative and learning perspectives, internal business, customer as well as fi-nance.
One major weakness is that the model does not integrate a competitive meas-ure and a human resource viewpoint. Another framework developed involves the working functions of an organisation, which measures the satisfaction of the stakeholder in a combination of determinant factors such as stakeholders’ con-tribution, capabilities, processes as well as strategy. De Toni and Tonchia (2002) developed their own model to improve this list and created the frustum model, which disconnects customary cost performance measures like productiv-ity and cost production from the non-cost method such as flexibility, time and quality.
These models help to differentiate between internal cost and non-cost as well as external performance. However, this provides a valuable classification of the most universal measures on a planned level that are required to explore ramp-up performance on a more effective level. One major problem is creating a ramp-up performance measurement system that is reliable with the general business goals and does not result to disagreements between the different functions that constitute the model. Also, another issue with the performance measurement is based on the fact that it is so diverse and the various aspects of performance measurement system design are independent of the other.
One very important aspect of production ramp up is proper understanding of the various requirements of the distinct customer segments that are used to make an efficient supply chain (Petersen et al 2005). On the other hand, operational performance is regarded as a high percentage of sold products with the suppo-sition of a very effective capability utilisation rate of the mechanised system. The time period immediately after the ramp-up begins is very critical due to the promotion and sales activities that are already started while lots of configuration and improvement activities are still in progress. Particularly in projects with a well-built intention on time to market, the various project teams constituting the system strive for accelerated product growth, often opposing the time achieved in earlier stages of the development cycle throughout an unproductive ramp-up that come as result of heavy ramp-up problems. Karlsson and Ahlström (1996) puts forwards that efficient ramp-ups are categorised by a greater operational performance, where efficiency is made to measure how an organisation’s re-sources are economically utilised.
To measure the operational performance throughout this phase, it is only advis-able to measure the real invoiced quantity over a given time period and esti-mate the ratio with the established quantity for that period. This presents a closer relation to profitability than those measures that are entirely based on manufacturing output. For instance, any mechanised output that is achieved based on plan but manufactured to stock or without established account would definitely demonstrate a strong manufacturing performance which does not in any way contribute to profitability. More so, manufacturing output that contrib-utes greatly to profitability has to be achieved with a high rate of capacity utilisa-tion.
Sánches and Peréz (2001) established other measures to indicate production performance and divided these into five different groups:
Elimination of zero-value activities; this is measured by six different indi-cators: The percentage of common parts in company products should in-crease, the value of work in progress in relation to sales should de-crease, the inventory rotation should increase, the number of times and distance parts are transported should decrease, the amount of time needed for die changeovers should decrease and finally the percentage of proactive maintenance should increase.
Continuous improvement; this is measured by eight different indicators: The number of suggestions per employee and year should increase, the percentage of implemented suggestions should increase, savings and benefits from the above should increase, the percentage of inspections carried out by autonomous defect control should increase, the percent-age of defective parts adjusted by production line workers should in-crease, the percentage of time machines are standing still due to mal-function should decrease, value of scrap and rework in relation to sales should decrease as well as the number of people primarily dedicated to quality control.
Multifunctional teams; this is measured by five different indicators: The percentage of employees working in teams should increase, the number and percentage of tasks performed by this teams should also increase, the percentage of employees rotating within the company should in-crease, the average frequency of task rotation should increase and finally the percentage of team leaders that have been elected by their own co-workers should increase.
Just In Time (JIT) production and delivery; this is measured by five dif-ferent indicators: The lead time to customer should decrease, the parts delivered by suppliers JIT should increase, the level of integration be-tween suppliers and the customer company should increase, the per-centage of parts delivered JIT between sections within the company should increase and at last the production and delivery lot sizes should decrease.
Suppliers integration; this is measured by seven indicators: The percent-age of parts designed in cooperation with suppliers should increase, the number of suggestions made to suppliers should increase, the frequency of visits by the suppliers technicians should increase, the frequency of visits to the suppliers by the customer companies technicians should in-crease, the percentage of documents interchanged with suppliers should increase, the average length contract with strategic suppliers should in-crease and finally the average numbers of strategic suppliers should de-crease.
A considerable amount of an organisation’s business is made up of business to business transactions which require that every participant plays a major func-tion. Under these circumstances the violation of approved dates of delivery could result in punishment clauses or lost sales with a negative effect on the product business in general, the concentration on pure ramp-up speed is eco-nomically not wise since lack in quality and other cost drivers can build up to a level that can sustainably affect the general company competitiveness (Twigg 1998). Also, meeting up customer requirement of this nature requires excel-lence in flexibility and dependability. These dimensions are measured using the ratio between the real production result over a specified time period and the es-tablished sales quantities that have been decided within that time before the ramp-up begins. This ratio provides an idea of the general planning exactness of new products that is also reproduced in the financial reporting of the corpora-tion (Kaski 2002).
Twigg (1998) claims that it is crucial to determine the type of relationship the suppliers are in with the customer company before ramp-up begins as well as deciding upon location of authority and responsibility in order to maximize coor-dination. Also a timeframe within a specified time period has to be chosen as a result of the launch procedure and ordering of long lead-time mechanisms that has to be put into use before the ramp-up begins. Pufall et al (2007) explained that, in an environment that is characterized by steady volume estimates this procedure would be adequate. Though, due to environmental effects activated by competitor performances, portfolio changes as well as new technology open-ings and ramp-down decisions for other projects, the volume estimate is highly unbalanced. Integrating this feature in the calculation alters the reliability ratio of the change in market demand. For instance, a product ramp-up could perform very well if it is calculated based on the earlier agreed numbers and at the same time, could still lose a significant opportunity if the market demand would in-crease (Sharifi and Pawar, 2002).
A prospective weakness of this system of measurement is that, it assumes the ramp-up speed will be synchronized and made to achieve maximum profitabil-ity. This is basically guaranteed by normal reassessment of the product busi-ness case established by the product program manager but ramp-ups in fast manufacturing or producing industries with corresponding short lifecycles will always face the predicament that they have to make steady asset investments rates, material risk orders as well as the obtainable ramp-up speed. Hilletofth et al (2010) mentioned that companies should focus their efforts on developing customer oriented business models by organising themselves in such a way that they understand the customers’ needs and identifies customer value as well as understanding how this value can be delivered to the customer. Also the companies must obtain the knowledge of how the processes within the supply chain effects one another and how these can be coordinated.
Conventionally, quality has been defined based on conformance to measure-ment provided. Therefore, quality-based measures of performance have con-centrated on issues like the cost of quality. With the introduction of total quality management (TQM) the importance has shifted away from order qualifiers to requirement towards order winners that delivers consumer satisfaction or quality that exceeds customer’s expectations. Brooks and Schofield (1995) explained that, this is still considered as one of the most significant performance indicators in the high-technology and manufacturing industries as it emphasis on the con-cept of customer retention and lost sales, even though it is one of the most complicated indicators to measure. Several factors like service, price, design and functionality together with device reliability have effect on customer per-ceived value, considering greatly the general performance of an organisations manufacturing and delivery performance. In order to fulfil this, the company must understand the market and deliver the factors that are essential for the customers at focus.
Consequently, the focus is more on the issues that results in providing an ideal order to customers than on the observation of the customer towards the new product and effective service. The proportions that are associated with a perfect order are complex and comprise issues like non-damaged delivery, accessibility and functionality of all items and also accurately picked orders. Higher manufac-turing equipment, tools investments as well as resources for early risk orders using possible undeveloped material would tolerate for more improved ramp-ups, but only at the expense of risk and cost involved (Terwiesch et al 2001). To calculate these dimensions in excess of the ramp-up period, the return rate of the initial delivery batches, as a proportion of the total deliveries would include two measures such as time to market as well as pure cost measures. However, time to market and pure cost measures are significant performance measures, even though they constitute a negative effect relying on them during new prod-uct ramp-ups. In the short term, the effects of cost on the general profitability are small, but evidently constitute changes in the mid as well as long term.
Any lost sales and apparent lost profits in a fast clock speed industry will offset all the other potential efficiencies in the value chain by a clear margin. Manufac-turing companies are faced with increased global competition and are operating in markets that pursue more frequent innovation as well as higher quality. This results in that companies can only outperform competition by offering superior value, either by lower cost or by providing superior benefits for the customers (Hilletofth, 2008). Regarding time to market, Clark and Fujimoto (1991) consid-ers this as a significant dimension of product development performance, even though time to market is not integrated in their model due to the fact that, time to market is often calculated as the time involving sales start as well as concept generation. And also, it is more an assessment of product development per-formance than of ramp-up performance.
Secondly, the model follows the hypothesis taken by Mallick and Schroeder (2005) who argue that time can rather be considered as a valuable resource. In-tegrating the concept of time to market as a significant variable of the new product development procedure as a dependable factor within the product de-velopment area into a single conceptual model. There is experimental evidence that amplified pressure on time to market during new product development pro-
jects could greatly reduce development time but at the cost of other perform-ance measures such as ramp-up quantity, quality as well as effort.
Conceptual Model and Propositions
Conceptual models as well as propositions are normally defined and quantify well known characteristics into more elaborate and detailed relationships be-tween the various characteristics so as to generate a comprehensive concep-tual model (Brown et al 1997). Initially, a regroup function will be performed on the seven identified characteristics (related to the manufacturing strategy, non financial measures, similar measurement systems at different locations, change over time if needed, simple and easy to use, provides fast feedback and finally intended to foster improvement) into major categories that make available the headers for the subsequent sub-sections that include the external environment, logistics system, the product development process, the manufacturing capability as well as the product architecture. This grouping supports the identified fea-tures with experience and observations from an organization’s specific envi-ronment. Also, it is observed that the outstanding elements, which involve the human resource group or the practice and usage of tools, are either suitable to all of the features or just part of the main characteristics. The product architec-ture is made up of all the physical as well as functional items that are required to fulfil the customer needs. The product architecture is also the planning of the functional elements of a product into the various physical blocks (Clark and Fujimoto, 1991). The product architecture generally starts to appear during the concept formation phase and becomes more complicated during the develop-ment phase by choosing major design suppliers, technologies, components as well as variables.
CHAPTER ONE: INTRODUCTION
1.2 Aim of study
1.3 Research Questions
1.4 Significance of the Study
1.5 Methodology of the study
1.6 Content of the chapters
CHAPTER TWO: THEORETICAL FRAMEWORK
2.2 Product Development Analysis
2.3 Product Development Performance
2.4 Relationship between Ramp-up Product Development and Performance
2.5 Capabilities for Rapid Supply Chain Operations Ramp-up
2.6 Ramping up Quickly
CHAPTER THREE: RAMP UP PERFORMANCE ANALYSIS
3.1 Ramp-up Performance
3.2 Conceptual Model and Propositions
CHAPTER FOUR: THE SUPPLY CHAIN RAMP-UP PERFORMANCE CAPABILITIES
4.1 Front End
4.3 Value Delivery
4.6 Product Development Process
CHAPTER FIVE: EMPERICAL FINDINGS
5.1 Effective Integration with Customers and Suppliers
5.2 Ramping up Quickly by the use of Outsourcing
5.3 Effects of failure or success in Ramp-up
5.4 Collaboration and value delivery
CHAPTER SIX: CONCLUSION AND DISCUSSION
6.3 Further research
CHAPTER SEVEN: REFERENCES
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