Short-run Production Research Articles

A visual imitation learning algorithm for the selection of robots’ grasping points

The short-run production and customization are increasingly common in the manufacturing industry, which results in the frequent adjustments of production lines. Industrial robots in these production lines are also required to quickly learn to perform new grasping tasks. However, the traditional approaches in grasping points selection, which rely on the geometric envelope models of objects in preset task space, can no longer meet the demands of fast-shifting production. Therefore, the present paper tackled the problem of grasping points selection with a novel CNN-based imitating learning framework. Our imitating model learns the correct grasping posture for objects from human grasping operations captured on camera. The experiments showed that this imitating learning algorithm can help a dual-arm robot master the correct grasping posture of an object within only 20 min. Compared to traditional geometric modeling-based methods, such as the pick-and-place module available in the Robot Operating System (ROS), this new approach can increase grasping planning efficiency by 26.1%.

Weather the storms? Resilience investment and production losses after hurricanes

This paper studies whether resilience investment mitigates damages from extreme weather events using data on offshore oil production in the Gulf of Mexico. We show that hurricanes which pass near rigs lower production and that stronger storms have larger impacts which persist for months. Regulatory changes that required rigs be designed to be resilient to major hurricanes only modestly mitigated the short-run production losses from hurricanes, reducing oil production losses by roughly 5% at 1 month and 20% 8 months after impact. They also only partly mitigated long-run losses, lowering the probability that a rig permanently exits production by 12–18 percentage points after a hurricane.

Russia–Ukraine war: A note on short-run production and labour market effects of the energy crisis

We provide first causal evidence of effects of the energy crisis on Germany, the largest economy in Europe. Combining cost structure data, national accounts and administrative labour market data, we identify effects in a sectoral panel setting using sector-specific energy intensity as a “bite” variable. The results show that through the channel of energy intensity, monthly production and real turnover decreased by 4.1 and 2.6 per cent, respectively, after the onset of the Russia–Ukraine war. Instead of layoffs, firms safeguarded employment by means of short-time work, with a 24.1 per cent increase in notifications. Vacancy posting was reduced by 10.3 per cent.

VAT elasticity on Nepalese economy without agriculture

This paper seeks to examine the elasticity of Value added tax (VAT) on Nepalese economy without agriculture. It, therefore, analyzes the impact of VAT on GDP in aggregate level without agriculture. This study adopts explanatory research design and attempts to determine the relationship between VAT and the GDP, exchange rate, market capitalization money supply and government spending being the intervening variables included in the model. In order for the specification of a model of cointegrated regression model with a time series data of the variables are employed for the study period of 20 years, from 1998/99 to 2017/18. The values of all the variables are converted into real price (constant price) by GDP deflator. The GDP deflator and CPI year 2013/14 have been assumed equivalent to the base year 2013/14 according to Nepalese fiscal year. Since it is observed that residuals are not normally distributed, autocorrelation and multicollinearity problem in the model, it is necessary to improve the non-normal distribution, autocorrelation and multicollinearity problem in the model. Therefore, the data are transposed into first difference and run the model with error correction model. The diagnostic test suggests that the residuals do not violet classical assumptions. The lagged residuals from 5.7.2 equation of Table 5.9 are statistically significant indicating the acceptable ground to take variable as cointegrated set. The result allows long-run and short-run dynamics of all the relationship between GDPWA and VAT. The estimated coefficient of VAT in error correction model shows that one percent point rise in VAT has led to 0.438 percent point increase in real GDPWA in short-run, whereas it is found 0.558 percent point in long-run. It means that short-run marginal productivity of VAT is 0.438 percent point, whereas its long-run percent point is 0.558.

Optimal design of S2‐EWMA control chart for short production runs

AbstractIn recent fast pace smart manufacturing environment, the short production runs (SPR) control charts offer a higher degree of flexibility compared to the traditional control charts. This is due to Phase I data collection not needed for SPR control charts and this eases practitioners in estimating the parameters and setting up the control charts. This paper proposes the methods to optimally design the SPR S‐chart and SPR S2‐EWMA control chart for process variance monitoring in terms of truncated average run length (TARL), truncated standard deviation of the run length (TSDRL), and expected truncated average run length (ETARL) performance measures. The optimal parameters in minimizing the TARL and ETARL values for SPR S2‐EWMA control chart are presented. The control chart performances are compared between both the SPR S‐chart and SPR S2‐EWMA control charts. Results show that SPR S2‐EWMA control chart has a higher chart sensitivity and it triggers the out‐of‐control signal faster than the SPR S‐chart. An illustration using the real electronic manufacturing industry data is given in this paper to explain the implementation of the SPR S‐chart and SPR S2‐EWMA control chart.

Analysis of Traditional and Fuzzy Quality Control Charts to Improve Short-Run Production in the Manufacturing Industry

Quality control charts are limited to controlling one characteristic of a production process, and it needs a large amount of data to determine control limits to control the process. Another limitation of the traditional control chart is that it doesn’t deal with the vague data environment. The fuzzy control charts work with the uncertainty that exists in the data. Also, the fuzzy control charts investigate the random variations found between the samples. In modern industries, productivity is often of different designs and a small volume that depends on the market need for demand (short-run production) implemented in the same type of machines to the production units. In such cases, it is difficult to determine the control limits for the operations carried out on the same machines. This work aims to compare the traditional control charts and the fuzzy control charts for short-run production. In the traditional case, the data collected were processed using the (Minitab 21) software. It was found that the fuzzy control charts were more flexible and accurate in determining the control limits of the machine under study. The traditional deviation from nominal control charts showed false alarm of observation (15) as out-of-control, while the fuzzy (DNOM) showed that these observations were under control. Also, the standard deviation of the process was dropped from (σ =0.209041) to (σ =0.204401) after using the fuzzy control chart.

A Short-run Indirect Production Function

A Short-run Indirect Production Function

Do Agricultural Supports Affect Production? A Panel ARDL Analysis of Turkey

One of the controversial issues in the trade negotiations carried out with the World Trade Organization deals with agricultural supports related to production, which is claimed to disrupt the market system by creating an imbalance in supply and demand in the domestic market and to cause world trade contraction. In this context, the aim of this study is to examine the production effect of the deficiency payments and land-based direct supports widely used in Turkey. The study conducts a panel autoregressive distributed lag analysis for 11 selected agricultural products (wheat, corn, sunflower, seed cotton, paddy, soybean, canola, safflower, tea, dried beans, and olives) for the 2002-2019 period. The findings from the study are as follows: i) Increases in deficiency payments and land-based direct supports increase short and long run production. However, land-based direct supports have less of an effect on production. ii) While increases in input prices have a negative short run effect on production, the long run effect is the opposite. iii) Agricultural product price is not an important indicator for producers. This finding can be explained by the fact that farmers accept agricultural supports as a complement to the price variable in their production decisions. iv) Increases in the minimum wage added to the model based on Turkey’s structural characteristics have a negative long run impact on production. v) No statistically significant relationship exists between the number of tractors used to represent agricultural mechanization and the amount of production.

Alternate Wetting and Drying as Water-Saving Technology: An Adoption Intention in the Perspective of Good Agricultural Practices (GAP) Suburban Rice Farmers in Thailand

The alternate wetting and drying (AWD) as water-saving technology aligns with the good agricultural practices (GAP) principles, particularly in the environmental management of water conservation. Thus, GAP adopters as farmer groups are seen as viable AWD adopters in the initial stages of scaling out the adoption in Thailand. However, the understanding of integrating AWD as water-saving management among GAP adopters remains scant. Using the case of rice GAP farmers in Thailand, the study found a higher probability of adoption intention among GAP compared to non-GAP. AWD perceived advantage, knowledge, and the suitability of rice farms for AWD adoption trials are positively associated with higher adoption intention. While higher fixed cost lowers the probability of adoption, variable cost is positively associated with higher adoption intention in the short-run production decision. In order to scale out the adoption of AWD, farmers’ understanding of the safe and proper application of AWD, together with assistance for crop insurance in the case of crop failure, will be crucial. Risks connected with the adoption decision continue to be the biggest barrier to adoption, especially among small-scale farmers.

Market selection and product positioning decisions’ implications for short- and long-term performance: evidence from the US music industry

PurposeThis research paper aims to investigate detailed relationships between market selection and product positioning decisions and their associated short- and long-term product performance outcomes in the context of the music category: a cultural goods industry with high amounts of product introductions. Market selection decisions are defined by the size, competitiveness and age of market subcategories within an overall product category. Positioning decisions include where a product’s attributes are located spatially in the category (periphery versus the market center), whether a product resides within a single subcategory or spans multiple ones and what brand strategy (single versus co-branding) is used.Design/methodology/approachData are from multiple sources for the US music industry (aka product category) from 1958 to 2019 to empirically test the hypotheses: genres (rock, blues, etc.) correspond to subcategories; artists to brands; and songs to products. Regression analyses are used.FindingsA complex set of nuanced results are generated and reported, finding that key marketing decisions drive short-term new product success differently and frequently in opposing ways than long-term success. Launching into very new, well-established or very competitive markets leads to the strongest long-term success, despite less attractive short-run prospects. Positioning a product away from the market center and spanning subcategories similarly poses short-run challenges, but long-run returns. Brand collaborations have reverse effects. Short-run product success is found, overall, to be difficult to predict even with strong data inputs, which has substantial implications for how firms should manage portfolios of products in cultural goods industries. Long-run product success is considerably more predictable after short-run success is observed and accounted for.Originality/valueWhile managers and firms in cultural goods industries have long relied on intuition to manage market selection and product positioning decisions, this research tests the hypothesis that objective data inputs and empirical modeling can better predict short- and long-run success of launched products. Specific insights on which song characteristics may be associated with success are found – as are more generalizable, industry-level results. In addition, by distinguishing between short- and long-run success, a more complete picture on how key decisions holistically affect product performance emerges. Many market selection and product positioning decisions have differential impacts across these two frames of reference.

Developing a novel high-strength Al–Mg–Zn–Si alloy for laser powder bed fusion

Additively manufactured (AM) aluminium alloys have attracted increasing attention due to the great demand of prototyping, spare parts supply, short run productions and further light-weighting of vehicles. However, most of the reported AM aluminium alloys are usually modified version of commercial cast or wrought aluminium alloys. In this work, we successfully developed a new high-strength and ductile Al5Mg3Zn2Si alloy, which is designed for laser powder bed fusion (LPBF) process. The optimized relative density of 98.9% was obtained at a volumetric energy density (VED) of 129.1 J/mm3. The as-LPBFed Al5Mg3Zn2Si alloy features refined equiaxed α-Al grains and Al–Mg2Si eutectic network. In addition, the sub-micrometre sized, coherent α-Al(Fe,Mn)Si and MgZn2 dispersoids in conjunction with high number density of (Mg,Zn)-rich GP zones co-contribution to the excellent combination of mechanical properties, i.e. the ultimate tensile strength of 548 MPa, the yield strength of 403 MPa, and the elongation of 6.7%. Such a high-strength and ductile AM aluminium alloys without any addition of costly alloying elements has a great potential for automotive and aerospace applications.

ADDITIVE MANUFACTURING IN TURBOMACHINERIES

The primary objective of this paper is to discuss the recent advancements of Additive manufacturing in the field of turbomachinery. The most challenging thing in real world is fabricating a large turbine or a propeller with short production run, less tool investment cost and finally less carbon print. Additive manufacturing not only achieves this but also provide several advantages over conventional machining process. This paper aims to elaborate current trends in additive manufacturing methods, history of AM, its advantages and challenges and AM’s role in making the turbomachinery manufacturing easier.

Impact of Climatic Conditions on Rice Crop of Pune Division: A Geographical Analysis

The climate can thus be viewed as a mixture or aggregate of weather. Weather describes conditions of the atmosphere over a short period of time, and climate is how the atmosphere behaves over relatively long periods of time. The World Meteorological Organization (WMO), 30 years is the classical period for performing the statistics used to define climate. As a consequence, the 30-year period proposed by the WMO should be considered more as an indicator than a norm that must be followed in all cases. Climate is thus now more and more frequently defined in a wider sense as the statistical description of the climate system. This includes atmosphere, hydrosphere, lithosphere and biosphere of the interactions between them (IPCC, 2007). Climatic conditions help to shape various ecosystems and habitat around the globe. The climatic factors are impact on physical features as well as human life. It is a major role play in human environment and they also effects on his food, clothing, dwellings, and their occupations. Agriculture, our primary source of food, is critical for human survival, but its importance for the environmental climate. The agriculture system are depends on the climatic conditions and that’s view presence agriculture is an uncertain. The plants and animals are affected by atmospheric conditions; it is not unreasonable that we should expect man to show effects of a similar (Robert, 1907). Agriculture and climate are two broad factors effect on crop and livestock. Climatic conditions effects on the distribution of crops, livestock and their productivity (Madhuri S., 2003). The crop growth and its productivity are declining due to increase in temperature, declining organic matter of soil and increase rate of evapotranspiration. The temperature and humidity increase in summer and winter season to increase pests, diseases and weeds. Changes in precipitation pattern increase the likelihood of short run crop failure and long run production declines (Crosson, 1997).

A Qualitative and Quantitative Occupational Exposure Risk Assessment to Hazardous Substances during Powder-Bed Fusion Processes in Metal-Additive Manufacturing

Metal-additive manufacturing (AM), particularly the powder-bed fusion (PBF) technique, is undergoing a transition from the short-run production of components to higher-volume manufacturing. The industry’s increased production efficiency is paired with a growing awareness of the risks related to the inhalation of very fine metal powders during PBF and AM processes, and there is a pressing need for a ready-to-use approach to assess the risks and the occupational exposure to these very final metal powders. This article presents a study conducted in an AM facility, which was conducted with the aim to propose a solution to monitor incidental airborne particle emissions during metal AM by setting up an analytical network for a tailored approach to risk assessment. Quantitative data about the respirable and inhalable particle and metal content were obtained by gravimetric and ICP-MS analyses. In addition, the concentrations of airborne particles (10–300 nm) were investigated using a direct reading instrument. A qualitative approach for risk assessment was fulfilled using control banding Nanotool v2.0. The results show that the operations in the AM facility are in line with exposure limit levels for both micron-sized and nano-sized particles. The particulate observed in the working area contains metals, such as chromium, cobalt, and nickel; thus, biological monitoring is recommended. To manage the risk level observed for all of the tasks during the AM process, containment and the supervision of an occupational safety expert are recommended to manage the risk. This study represents a useful tool that can be used to carry out a static evaluation of the risk and exposure to potentially harmful very fine metal powders in AM; however, due to the continuous innovations in this field, a dynamic approach could represent an interesting future perspective for occupational safety.

An intelligent manufacturing cell based on human–robot collaboration of frequent task learning for flexible manufacturing

The trend of short-run production and personalized customization is more and more popular in the manufacturing industry. And the robots in these production lines must conduct task adjustment efficiently when learning new tasks. Thus, this paper developed the intelligent manufacturing cell based on the human–robot collaboration (HRC-IMC) which can enhance the learning ability of cobots by introducing the intelligence of human. The HRC-IMC was composed with four modules: the imitating learning module, the human–robot safety planning module, the task planning module and the visual inferring module. All of the four modules were designed to provide a set of systematic and effective methods. That was conductive to the efficiency improvement of the task adjustment for cobots’ new task learning. The experimental results indicated that the efficiency of task adjustment can be increased by 42.8 % when the HRC-IMC was employed than that of Moveit. All in all, this study is of great significance for improving the efficiency of new task adjustment of cobots by imitating the manipulation experience of human via combining four algorithm modules.

An analysis of OPEC oil production reaction to non-OPEC oil supply

This paper examines the impact of non-OPEC oil supply on OPEC oil production level at different quantiles of the OPEC production empirical distribution. It employs the Quantile Autoregressive Distributed Lags (QARDL) model that allows to probe simultaneously short-term connections and long-run cointegrating relationships across a range of quantiles. The analysis is undertaken using monthly data from January 1993 to March 2020.The main findings show that the influence of non-OPEC production on OPEC production is symmetric in the long-run but quantile-dependent in the short-run. In the short-run OPEC production decreases significantly following an increase of non-OPEC production. However, in the long run, the increase in non-OPEC production causes OPEC production to rise. Furthermore, the results show that oil prices increase OPEC production in the long- and short-run. The potential policy implications for OPEC and non-OPEC oil production are discussed.

Management of Business Processes in Short-Run Production

Management of Business Processes in Short-Run Production

A new EWMA median chart with measurement errors in short production runs–An application in yogurt cup filling process

AbstractThis article presents an exponentially weighted moving average (EWMA) median chart for short production runs (SPR) (called EWMA SPR median chart). This chart improves the sensitivity of the Shewhart median chart for SPR (called Shewhart SPR median chart) proposed by Khoo et al15 in the detection of mean shifts. The proposed chart's performance is evaluated by means of the truncated average run length (TARL), truncated standard deviation of the run length (TSDRL), and expected TARL (ETARL) criteria. For all sizes of mean shifts, regardless of the sample size, the findings show that the EWMA SPR median chart outperforms the Shewhart SPR median chart. The EWMA SPR median chart is also investigated when measurement errors are present, as these errors affect the chart's performance. An example is given to illustrate the working of the chart when measurement errors are present.

Overview on the digitized production of welded steel structures

This paper presents a concept and practical topics involved in digitized production. The term “production” denotes the design, fabrication, and service life of a product, which in this case elaborates on welded steel structures. This includes the required information for guiding all the process stages of the chosen material back to its re-melting, following the material flow in a fully digitized form. This concept enables an increase in production quality at a higher level while minimizing the risk of human errors. Automation of the short-run production of steel structures for demanding applications is also a key goal, together with securing a cost-efficient process. Typically, such structures are fabricated from high- or ultra-high-strength steels. Though challenging, reaching these aims seems to be realistic by applying advanced fatigue design methods, using high-quality robotic welding and receiving information about the real loading of the structure.

Comparison of short runs control chart and T2 Hotelling control chart for monitoring sunergy glass production process

In recent years, the manufacturing industry has tended to reduce mass production and produce in small quantities, which is called “Short Run Production”. In such a situation, the course of the production process is short, usually, the number of productions is less than 50. Therefore, a control chart for the short run production process is required. This paper discusses the comparison between multivariate control chart for short run production (V control chart) and T2 Hotelling control chart applied to sunergy glass data. Furthermore, a simulation of Average Run Length (ARL) was carried out to determine the performance of the two control charts. The results obtained are that the production process has not been statistically controlled using either the V control chart or the T2 Hotelling control chart. The number of out-of-control on the control chart V using the the EWMA test is more than the T2 Hotelling control chart. Based on the ARL value, it shows that the V control chart is more sensitive than the T2 Hotelling control chart.