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Distinction between start-up and ramp-up [5] 

Distinction between start-up and ramp-up [5] 

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Article
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Companies that introduce new products quickly have been shown to be better performers. The effectiveness of the new product introduction process is critical to their performance. Production ramp-up is a necessary phase of new product introduction and both planning and execution need careful consideration especially for engineered products which are...

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... volume, yield and costs are reached" [11] Authors agree on the steep increase of output rate reported during this phase, but they disagree about the chronological limits of the process. Moreover, sometimes terms such as ramp-up and start-up are used interchangeably (start-up is the whole phase of output rate increase; ramp-up is only the phase during which a steep rise of the output rate is verified [5], see Figure 1). Indeed, sometimes the earlier part of the start-up is so short that the two terms coincide. ...

Citations

... The simulation was carried out for varying levels of rampup maturity in the automotive industry with the aid of capability curves. Ball et al. (Ball et al., 2011) carried out the modelling production ramp-up of engineering products. The study presented a framework through which production ramp-up of engineering products can be modelled. ...
... Learning by doing is a natural phenomenon that improves human performance, and it leads to a reduction in the time required to perform an activity for each repetition [24]. In 1936, Wright noted that when doubling the produced volumes, the unit production time was reduced by a constant percentage [25]. ...
... The curve can be used to derive the time spent by employees to learn a new activity and, consequently, plan the workforce during full production. In the same context, Ball et al. (2011) [24] affirm that the opposite phenomenon to learning, namely the tendency to forget, must also be considered in formation. In the field of industrial engineering, the common assumption is that if the worker interrupts the execution of activities for a certain period, then the performance of the worker deteriorates up to when a new production session begins [24]. ...
... The curve can be used to derive the time spent by employees to learn a new activity and, consequently, plan the workforce during full production. In the same context, Ball et al. (2011) [24] affirm that the opposite phenomenon to learning, namely the tendency to forget, must also be considered in formation. In the field of industrial engineering, the common assumption is that if the worker interrupts the execution of activities for a certain period, then the performance of the worker deteriorates up to when a new production session begins [24]. ...
Article
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The initial adoption phase of new production technologies is the period between the first production run or technology reconfiguration and the achievement of a stable target output. This time frame is generally characterized by productivity unsteadiness, quality performance variability, and unexpected machine failures together with increasing production volumes due to the process setup and instability, which inevitably affects production output. In this context, human performance represents an additional source of variability and process instability that is dependent on the workers’ productivity, learning curve and related training activities. Hence, to effectively assess the ramp-up phase of new production technologies, an appropriate evaluation of human performance is required. This paper proposes a comprehensive framework and criteria to perform a consistent assessment of the initial adoption phase of new production technologies by introducing two OEE measurement methodologies that distinguish between human performance, process configuration and technical features of the production technology. The proposed framework is then applied to and validated by a case study concerning the introduction of a semi-automatic packaging machine in a primary multinational company in the logistics industry. This case study shows the difference between the two OEE measures, along with the values interpretation and useful insights for achieving a stable production output.
... On the one hand the common breathing devices, without mechanical support, work on affected people without severe symptoms while on the other hand the Continuous Positive Airway Pressure (CPAP) is form of non-invasive mechanical ventilation, working as breathing aid, which applies mild air pressure on a continuous basis and keeps the airways continuously open in patients who are able to breathe on their own, but they need help keeping their airway unobstructed (Ti, 2020). In addition, air control valves are responsible to control the oxygen that fills in the breath mask from an external respirator (Ball, 2011). Without these valves the patient mask is not capable to work. ...
... So, three stages can be pointed; a) pilot production when the first parts come out of the production and both the machines and the parts are under inspection to ensure, that the products follow the product requirements and the machines are in good condition; b) the low volume phase where the production line work at 50% of its potentials in order to control the production in terms of energy consumption, cost as well as the wear of machines; c) the high volume phase where the product quality, production volume, energy consumption etc. are optimized and they remain constant over time (Ball, 2011). The last term ramp up expresses the rate with a production can address all the knowledge obtained during the low volume production in order to move to high volume production or from pilot production to low volume production. ...
Article
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The unprecedented events that worldwide population experienced during year 2020 due to the COVID-19 pandemic, resulted in the formation of numerous challenges across the majority of aspects of every day life. Manufacturing industries and supply chain networks faced a unique decostruction during this period due to restrictions created by global or local lockdowns. Reduction of human resources availability and transportation restrictions linked with the extreme and rapid increase of demand for medical supplies led manufactring related activities to reach their limits. Moreover, the non flexible manufacturing methods that are employed for the production of this type of equipment as well as the delayed delivery of products that are used as raw material at the early production stages, resulted in market shortage of medical supplies while demand constantly growing. As a matter of fact, various production models and manufacturing processes had to be used at different phases, due to different levels of resilience. Automotive industry in particular tested corresponding processes' agility by transforming production and speeding up the production of medical equipment with alternative ways. However, the formal identification of the problem as well as the quantified requirements of each manufacturing method have to be evaluated in order to extract meaningful results that identify the reasons why traditional manufacturing facilities faced such difficulties in the production of medical equipment and to propose a roadmap where Additive Manufacturing methods can be used for the immediate, local and low volume production of the desired
... High variety production ramp-up is a critical step in product life cycle as it could lead to either success or failure of product introduction into the market [2] [6]. The criticality of this step is owed to several factors including the challenging costing and cost-benefit analysis tasks of unstable production [7]. Accordingly, this paper addresses the following questions: What are the challenges of ramp-up management particularly with regards to cost modelling and cost-benefit estimate? ...
... In their effort to consistently deliver customized products and services, companies are faced with a continuous multi-product development and ramp-up [1]. While ramp-up is very determinant phase in product life cycle, it received less attention than both design and stable production phases in particular considering high variety production environments [2][6] [7]. While there are several definitions of ramp-up, it is commonly accepted that ramp-up is the connecting phase between product development and series production [8]. ...
... lowvolume-high-mix) [2]. As a matter of fact, ramp-up management decisions particularly impact on and are impacted by capacity planning, learning effects and operations cost , which have in turn mutual influences [7][12] [13]. Capacity is usually limited at the beginning of and during the ramp-up phase, which requires increasing it incrementally in particular in high complexity production [13]. ...
Chapter
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Production ramp-up is a critical step in product life cycle as it could lead to either success or failure of product introduction into the market. The criticality of this step is owed to several factors including the uncertainty underlying this step regarding both expected costs and benefits, and thus to the complexity of decision-making. In order to enlighten decision makers particularly in multi-variant production contexts, this paper elaborates on an analytical model supporting cost-benefit analysis of production ramp-up strategies. The model takes into account capacity planning decisions and learning curves in determining cost-benefit estimates. The model is illustrated and discussed through a keyrings manufacturing process.
... The process of fine-tuning a production system exhibits some characteristics that make it difficult and time-consuming. Previous studies highlight the stochastic and sequential nature of the process with little knowledge of system's dynamics and its uncertain behaviour (Haller et al., 2003;Ball et al., 2011). According to Surbier et al. (2014) ramp-up phase is characterized by a low level of initial knowledge, throughput, and production capacity; high in cycle time, demand, and disturbances; and lack of planning reliability. ...
Article
Production ramp-up is a key phase during the introduction or changeover of a production system. Process calibration and tuning are inevitably required to make such a system fully operational and let it reach its maximum production yield. A complex decision-making process takes place in order to optimally tune the system and requires a long time for testing and experimenting that will determine the system behaviour. This work considers the sequential nature of ramp-up and proposes a Cyber-Physical Systems approach based on data capturing, learning mechanisms and knowledge extraction, leading to an Industry 4.0 compliant Decision Support System (DSS) for human operators. The proposed system is implemented as an online DSS and also supports offline learning using previously gathered knowledge. A number of experiments have been carried out on a micro scale assembly station, validating the expected benefits of the proposed DSS. Results show a reduction of over 40% in the number of ramp-up steps required when using the DSS.
... There is evidence that more than 50% of launches in the automotive industry do not meet their quality and production targets (Surbier, Alpan, andBlanco 2014, Straube, St€ oLzle, andSchuh 2008). Moreover, most of the economic losses caused by a decrease in productivity are mainly concentrated within the ramp-up phase (Ball et al. 2011;Almgren 2000). Gopal et al. (2013) conclude that the average launch costs between 43 and 52 million dollars, making this phase of the product an especially useful subject of study. ...
Article
Many new model launches in Europe do not meet the quality, cost and production targets set by automotive companies during production ramp-up. Although increasing car complexity could be a key factor in explaining this issue, it is not sufficient to explain why production sites are not able to meet these important targets. This article analyses whether the production system used in European car manufacturing plants are suitable for achieving performance goals during the production ramp-up phase. First, the differences between serial production and the production ramp-up phase are analyzed through the conceptual framework of the European Production System in the automotive industry. Second, a case study using real data from a European automotive plant is presented, and the evidence calls into question the appropriateness of maintaining the same production system during the ramp-up phase. The study concludes that there is a need to make the production system in Europe more flexible during the ramp-up phase. In particular, changes should be more oriented towards fostering organizational improvement capability in order to reduce the stops that occur in the production line, avoid using pull systems as a constraint or limitation, and help to build a new culture of stopping to fix problems.
... In the production ramp-up, we consider two types of expenses: recurring costs and non-recurring costs 43 . The recurring costs are incurred due to the production percentage increment x t /x t−1 , such as the labor cost to hire temporary employees. ...
Article
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Motivated by challenges in the smartphone manufacturing industry, we develop a dynamic production ramp-up model that can be applied to economically satisfy nonstationary demand for short-life-cycle products by high-tech companies. Due to shorter life cycles and more rapid evolution of smartphones, production ramp-up has been increasingly critical to the success of a new smartphone. In the production ramp-up, the key challenge is to match the increasing capacity to nonstationary demand. The high-tech smartphone manufacturers are urged to jointly consider the effect of increasing capacity and decreasing demand. We study the production planning problem using a high-dimensional Markov decision process (MDP) model to characterize the production ramp-up. To address the curse of dimensionality, we refine Monte Carlo tree search (MCTS) algorithm and theoretically analyze its convergence and computational complexity. In a real case study, we find that the MDP model achieves revenue improvement by stopping producing the existing product earlier than the benchmark policy. In synthetic instances, we validate that the proposed MCTS algorithm saves computation time without loss of solution quality compared with traditional value iteration algorithm. As part of the Lenovo production solution, our MDP model enables high-tech smartphone manufacturers to better plan the production ramp-up.
... This is because decisions about the logical or physical adjustments of the system are often made on a try and error basis. Nevertheless, Ball et al. [17] recognise the opportunity of being able to obtain performance improvements during ramp-up. This is seen in the introduction and first-time testing of novel production processes. ...
Conference Paper
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Nowadays, shorter and more flexible production cycles are vital to meet the increasing customised product demand. As any delays and downtimes in the production towards time-to-market means a substantial financial loss, manufacturers take an interest in getting the production system to full utilisation as quickly as possible. The concept of plug-and-produce manufacturing systems facilitates an easy integration process through embedded intelligence in the devices. However, a human still needs to validate the functionality of the system and more importantly must ensure that the required quality and performance is delivered. This is done during the ramp-up phase, where the system is assembled and tested first-time. System adaptations and a lack of standard procedures make the ramp-up process still largely dependent on the operator’s experience level. A major problem that currently occurs during ramp-up, is a loss of knowledge and information due to a lack of means to capture the human’s experience. Acquiring this information can be used to simplify future ramp-up cases as additional insights about change actions and their effect on the system could be revealed. Hence, this paper proposes a decision-support framework for plug-and-produce assembly systems that will help to reduce the ramp-up effort and ultimately shorten ramp-up time. As an illustrative example, a glueing station developed as part of the European project openMOS is considered.
... Every delay means that revenues can be lost and reputation of manufacturer can be damaged. For that reason, the start-up of a new production line is a key learning moment for organizations (Ball et al., 2011). ...
... When new manufacturing equipment is installed, usually it is not possible to produce high volumes instantly (Ball et al., 2011). But, as a solution EEM and EPM pillar endeavors to drastically reduce the time from initial development of a new product/equipment to full production capacity with the implementation of previously mentioned Vertical start-up -VSU principle. ...
Article
There is an obvious need to redefine approach to provide and develop human resources necessary for modern industrial systems and to find new models that will meet the demands of Lean philosophy and concepts of safety and ergonomics. The authors are suggesting Early Human Resources Management (EHRM) model, inspired by developed pillar structures of Lean based World Class Manufacturing (WCM) and Total Productive Maintenance (TPM) industrial systems and based on proactive approach referring to human resources. The EHRM model is designed through the integration of Early Management and Human Resources development concepts and uses the Vertical start-up (VSU) principle for a drastic reduction of time needed for reaching the full potential and achieving the desired level of knowledge and competencies of human resources in Lean industrial systems. Practical applications: EHRM contributes to reducing the gap between expected and real performances of human resources at an early stage of their professional careers and enables the effective and efficient transition from academic to industrial environment. At the same time, cooperation, communication and knowledge transfer between industry and universities are upgraded, development of educational curricula is facilitated and build around the applicative knowledge skills, and methods.
... 1 The ramp-up costs consist of three different cost blocks: average costs, ramp-up costs and lost sales. 2 It is worth noting that economic losses caused by decreasing productivity are estimated at between US$42 and US$53 million. 2 What is more important, these losses are mainly concentrated within the period of time corresponding to the ramp-up curve, which is the period that goes from the launch of the first series vehicle to attainment of the maximum planned volume. ...
... 2 It is worth noting that economic losses caused by decreasing productivity are estimated at between US$42 and US$53 million. 2 What is more important, these losses are mainly concentrated within the period of time corresponding to the ramp-up curve, which is the period that goes from the launch of the first series vehicle to attainment of the maximum planned volume. As a result, the specific weight of the losses incurred during the rampup period becomes even more significant. ...
... Ball et al. 2 conclude that there is no agreement among authors on the chronological limits of a launch. This situation leads us to study the various interpretations of this period that exist in the literature with the aim of providing with a definition that will guide future papers. ...
Article
The automotive sector, along with many others, has been subject to two key trends in recent times. The first relates to globalization, in other words, the incorporation of new markets and a growing demand that needs to be satisfied. The second concerns the high expectations of customers regarding quality and the on-going renovation of products. The incorporation of new markets results in the expansion of new production centres all over the world, making it necessary to synchronize launches in different parts of the globe. Furthermore, customers’ new demands cause shorter product life cycles. Time is seen as the main factor in the success of any new product launch. Particularly, the period that begins when the production has started in a production plant and continues until the planned production rate has been attained (the ramp-up curve). Because launches have become more frequent, the specific importance given to the life of the model is greater. This article has the following objective: provide a thorough review of the literature, focusing on this specific phase in the life cycle of a model in order to identify, compile and extract any relevant information that will enable us to build a theoretical framework for the ramp-up curve. The article begins by analysing the different interpretations of the phases of the launch stage of a new product that exist in the literature, and it concludes with the evidence that ramp-up curves are an item of scientific interest, where the 21% of the papers relating to this item are focused on the automotive sector, where planning and management are the most recurrent themes. Finally, two themes that remain open for further research are detected: the lack of structured organization during the ramp-up phase and knowledge transfer between different launches of the same product in different places.