Publications resulting from literature review and used in analysis
| Authors (year) | Description of measures | Economic effects | Ecological effects |
|---|---|---|---|
| Adeniji and Schoop (2021) | Multi-objective optimization using digital process twins and artificial intelligence algorithms | Process queuing time and costs improved by 93% Quality control pass rate increased by 5% | Total embodied energy reduced by 84% Scrap rate reduced by 2% |
| Aguado et al. (2013) | Optimized, more linear layout to reduce intermediate stocks and movements Additional and renewed machines to eliminate bottlenecks | Production capacity increased by 13% Production time reduced by 70% Reduced batch size (from 800 to 50 units) increased flexibility Needed space reduced by 25% | Consumption of primary energy per unit reduced by 82% Cumulative energy demand reduced by 78% Environmental impact of manufacturing processes reduced by 22% |
| Baldassarre et al. (2019) | Collecting and distributing residual CO2 and waste heat from industrial company into greenhouses | User save 50% energy costs 750 new jobs created Project makes no profit so far | Avoids burning of 55m m³ natural gas p.a. 135,000 t of CO2 emissions are avoided p.a. |
| Baumer-Cardoso et al. (2020) | Implementation of lean principles, esp. Kanban and change of lot size | Lead time and work in process reduced by 83% Processing time reduced by 14% Production volume decreased by 32% | Consumption of raw material reduced by 13% Energy consumption reduced by 14%, but water consumption increased by 206% |
| Belhadi et al. (2018) | Implementation of cellular manufacturing, continuous flow, supermarket pull system etc. | Production increased by 34% Time efficiency increased by 27% Changeover time reduced by 70% Defect rate decreased by 17% Total lead time reduced by 71% Availability rate increased by 2% | Electrical energy consumed per product reduced by 45% Water consumption per product reduced by 45% Consumption for crude metals per product decreased by 29% |
| Ben Ruben et al. (2017) | Modification of layout and equipment via SMED, audits etc. | Cycle time reduced by 18% Lead time reduced by 20% Rejection costs reduced by 85% | Net power consumption reduced by 25% Net water consumption reduced by 12% Raw material required to manufacture reduced by 20% |
| Buandra (2019) | Production optimization through motion and time study lead to cycle operation from every third to every fourth shift | Reduced ladle utilization due to reduced number of activities from 66 to 55 Standard time reduced by 10% (from 39 to 35 min/ladle) Operation hours are reduced by 21% for anode changing and by 11% for ladle transportation | Hydrogen fluoride emissions are reduced by 20.5% |
| Chompu-inwai et al. (2015) | Changes of material (wood type) and machine settings (blade angle, number of saw teeth) | System costs for cutting process decreased by 9% Energy costs for cutting process decreased by 13% Reduced material losses lead to cost savings of 16% | Material losses reduced by 22% |
| Choudhary et al. (2019) | Improving production via resource leveling, processes integration etc. | Reduced lead time by 63% Production efficiency increased by 33% Number of defects decreased by 57% | CO2 emissions reduced by 77% (net savings of 967t of CO2e per year) |
| Diaz-Elsayed et al. (2013) | Implementation of a combination of lean and green strategies (e.g. batch size reduction, use of energy-efficient engines) | “Green strategies” contributed 4.7% of the overall 10.8% savings in production costs compared to initial state | |
| Fahad et al. (2017) | Optimized layout reduces transportation effort and promotes maximum daylight usage | Costs for fuel und electricity decreased by 57% | Fuel consumed in material flow reduced by 62% Lighting energy consumption reduced by 57% CO2 emissions reduced by 58% |
| Felsberger et al. (2020) | Algorithm to rearrange furnace charging | Throughput increased by 7% due to heating time optimization of furnaces | Energy consumption reduced by 10% due to reorganization of the pre-heating furnaces |
| Fu et al. (2017) | Modification of equipment (mold, pipeline, ventilation), redesign and automation of cleaning procedure, improved accessory mixing | Processing time reduced by 15% Proportion of value-added process increased by 14% Total cost saving of CNY 14.1 m p.a. (initial investment of CNY 6.8 m) | Material and energy savings, pollution and waste reduction |
| Gholami et al. (2021) | Optimized chemical composition decreased bleed-off volume without affecting quality and effectiveness of the process Operating controller and sensors keep oven idle during non-activity | Significant cost savings | Consumption of chemicals reduced by 28% Energy usage reduced by 21% |
| Glick and Shareef (2019) | Optimization of electrostatic powder coat cure oven process | Process time reduced by 5% | Natural gas consumption reduced by 5% |
| Handoko et al. (2018) | Continuous improvement approach led to the installation of ammonia stripping equipment | Benefit of ammonia recovery of USD 3.4 m p.a Total investment of USD 1.3 m (payback period of 5 months) | Pollution by ammonia decreased by 65% BOD decreased by 3% COD decreased by 10% |
| Huang et al. (2017) | In-house additive Manufacturing (T) | Downtime could be reduced by 70–80% compared to conventional manufacturing Lead time reduced of 12–60% Cost per part are 15–35% lower | Energy consumption could be reduced by 3–5% GHG emissions could be reduced by 4–7% |
| Iqbal et al. (2015) | Fuzzy rule-based system leads to settings for the cutting parameters to optimize energy consumption, tool life and machining productivity | Increased feed rates reduce energy consumption; this ensures high productivity and reduced CO2 emissions | |
| Isasi-Sanchez et al. (2020) | Potential of additive manufacturing to industry (T) | Profit might increase by 4% (equivalent to an increase of 15% over the margin with traditional manufacturing and distribution) | Estimated consumption of material reduced by 12% Energy saving could reach 9% due to reduced transportation |
| Jarrell (1992) | New coating and laminating process | Increased flexibility | Resin usage reduced by 30% |
| Jayachandran et al. (2016) | Casting replaced by powder metallurgy process | Costs per part are three times higher than with casting Increased tool life on the machining centers | Material waste per part reduced by 76% |
| Khan et al. (2021) | Combination of cryogenic and minimum quantity lubrication (compared to flood cooling) | Unit production cost of new technology are around 27% lower, but environmental costs are higher | Depending on the use case (esp. cutting speed), the CO2 emissions per part produced are significantly higher No need for cleaning, recycling and disposal with new technology |
| Kluczek (2017) | Replacing machines (e.g. from plasma to laser cutting, shot-blasting instead of sand blasting), installation of ventilation and filtering systems | Total production costs reduced by 6% | Cutting process: dust emissions reduced by 50%, material waste reduced by 25% Blasting process: 258 t of sand are replaced by 4 t of steel shot Capture of 1,465 kg of VOC p.a |
| Leme et al. (2018) | SMED with focus on CO2 emissions | Idle and setup times reduced by up to 88% | Carbon footprint reduced by up to 81% |
| Lucato et al. (2015) | Six Sigma extended by environmental variables such as consumption of electricity and chip generation of CNC lathes (T) | Increase the eco-efficiency to about 20% (and reduction of cycle time by 4%) | |
| Mangili and Prata (2020) | Comparison of butane-based and benzene-based maleic anhydride manufacturing technology The butane route is considered to be 34% more eco-efficient | Butane process is 34% more profitable | Benzene process consumes less raw material (48%) and water (3%), and generates less wastewater (3%) Butane process consumes 28% less energy and emits 43% less CO2 |
| Marinelli et al. (2017) | Industrial symbiosis where non-marketable products and waste are used by livestock and other enterprises | Investment of EUR 0.4 m Production company can sell waste at a 120% higher price | Production waste destined for disposal will become second raw material for processing companies |
| Mashaei et al. (2011) | Optimization of pallet system (T) | Number of pallets and conveyor velocity can be increased | Energy consumption reduced by 61% (for one specific configuration) |
| Moreira et al. (2018) | Calibration of machines, creation of quick wash program, implementation of new additives and activators | Cost savings of more than 30% Average set-up time reduced by 26%, average OEE increased by 5% Average MTTR improved by 21%, average availability (MTBF) increased in two of three studied equipment Product quality improved by 5% | Isopropyl alcohol consumption reduced by 39% Cleaning solvent consumption reduced by 3% Additive consumption of fountain solution increased by 10% |
| Nakajima (2015) | Material flow cost accounting triggered change of manufacturing procedure | profits increased | Material losses of previously 32% was reduced by 80% |
| Ndikumana (2019) | Implementation of 5S, VSM and Kaizen Elimination of production processes and usage of energy-efficient tools and equipment | Cost savings for electricity of ZAR 139k p.a Reduction of rental costs of ZAR 293k p.a. since less space is needed Savings of ZAR 313k since industrial gases are no longer needed for heat treatment process Reduction of work-in-progress inventory improved cash flow by ZAR 166k Lead time reduced by 1.5 days (from 6.4 to 5.9) Yearly increase in total sales of 15,6% (ZAR 5.7 m) | Electricity consumption reduced by 32% Reduction in the usage of industrial gas Reduction in CO2 emission by 97 t p.a |
| Păltan et al. (2019) | Retrofitting the production lines with specific machines and merging or replacing production steps Eliminating tight places with additional machines | Turnover increased by at least 22% due to additional capacities Energy costs decreased by 19% | Generating electricity out of waste |
| Pampanelli et al. (2015) | Kaizen approach for improving environmental flows of mass and energy of manufacturing cells | Average cost reduction of 8% on cell level and 4.5% on value stream level Productivity in the use of resources increased by 12% | Average resources consumption reduced by 35% |
| Panjeshahi et al. (2009) | Re-circulating cooling water system with cooling tower and heat-exchanger network interaction (T) | Total cost reduction of 45% compared to conventional system design (300% higher capital costs, but only 31% of operating costs) | 46% of make-up saving, 93% of blow-down water saving Energy consumption reduced by 17% |
| Park and Park (2014) | Steam from waste incinerator is used instead of fossil fuel | Cost savings of over USD 4.1 m p.a Portion of fuel costs of total operating costs decreased by up to 29% | CO2 reduction of 45,500 t p.a SO2 reduction of 427 t p.a. fuel consumption reduced by 18,850 t p.a. |
| Parthasarathy et al. (2005) | Shift from end-of-pipe treatment towards in-process waste reduction | Overall cost savings of USD 1m Identification of saving potential of USD 3.3 m at installation cost of USD 6.3 m (payback period of 2 years) Costs for program was USD 305k | Total waste reduced by >50% Burning of 1.6 t p.a. of hazardous waste eliminated Off-site treatment of 0.5 m t p.a. of organic waste avoided Reduced need of fresh resources Reduced generation of by-products (70% on unit level, 17% on site level) Consumption of electricity reduced by 9.55 m kWh Annual fresh water and waste water demand was reduced by 3.7 m m³ and 1m m³ respectively |
| Pusavec and Kopac (2009) | Conventional coolants such as air, oils and aqueous emulsions are replaced by cryogenic fluids (esp. liquid nitrogen) | Production costs reduced by up to 70% (depending on cutting speed) Higher production rate (shorter cycle time) Higher coolant costs, but lower machining cost and tool costs per part No disposal costs and reduced power consumption | Hazardous oil-based emulsions are avoided No residues or contamination of workpiece, chips etc. |
| Roeckel et al. (1994) | Introduction of a new step in the reduction process that involves recirculation of the pumping water and treating (i.a. screening, flocculation, centrifugation) resultant effluents | Productivity increased by 7% Marginal profits are higher than the treatment cost for high technology plants, leading to a ROI of 53% after a 5-year period Total investment of USD 2.2 m | Reduction of COD by 91.6% |
| Rosen and Kishawy (2012) | Implementation of measures to reduce VOC emissions (i.a. switching adhesive, recycle solvent) | Savings of CAD 349k p.a. Payback period <2 years | Reduction of VOC emissions of 35% |
| Scharf et al. (2021) | Installation of modular gas-based burner technology Novel process and plant concept using transportable melting and holding system Process monitoring with sensors | Production costs decreased by 48% due to substitution of expensive electricity by cheap gas Average cycle time is reduced by 5% Better quality of products (tensile strength increases by 12%) No cleaning and degassing of the melt by eliminating pouring processes No overheating of the melt due to an improved transport process More flexible production, because several alloys can be produced simultaneously approaching a lot size of one Transportation can be performed by different vehicles | Energy demand to melt, transport and hold decreased by 36% Consumed electricity decreased by 94% and gas by 32% Accompanied CO2 emissions decreased by 41% |
| Sellitto et al. (2021) | Industrial symbiosis with eight dyadic or triadic relationships exchanging 300,000 t of by-products per year, comprising coal ash, mill scale, electric arc furnace dust, steam, zinc sludge, lead sludge and refractory lining leftover | Steelmaking Operational costs reduced by 30% Elimination of disposal costs Cost reduction in purchases because refractory manufacturer accepts returns as part of the payment in sales Cement manufacturing Cost reduction due to recycling of by-products Substantial reduction in manufacturing cost due to fly ash transfer from neighboring power plant Ability to produce pozzolanic cement as an additional product | Steelmaking Transfer of mill scale to cement manufacturer (safe destination for hazardous waste) Refractory liner manufacturer 1 t of recycled waste preserves 3 t of magnesite ore and 1 l of fuel oil (avoids 700 kg of CO2 emissions) Leftovers from manufacturing process route as raw material to concrete artifacts manufacturing and road paving |
| Sgobba and Meskell (2021) | Evaluation of an on-site cogeneration system (T) | Expected payback period of 6 years | CO2 emissions avoided in the first year are estimated to be 2,500 t |
| Silva et al. (2020) | Implementation of lean principles such as Kaizen, Jidoka and TPM | 33% reduction of cycle time (on average) leading to savings of EUR 124/month of energy costs Savings of EUR1,000/months due to scrap reduction Percentage of rework fell from 15 to 4% (now 0.5 h per worker and day instead of 1.5; saving EUR 410/month for labor costs, welding shield gas and energy) Reduced over-processing | Energy consumption reduced by 38% Scrap reduced by 66% (400 kg per month) Reduced consumption of welding shield gas due to reduced rework Average reduction of 30% (ca. 3.5 kg) in raw material used in each product Reduction of 70% of the chemicals used for cleaning |
| Sobral et al. (2013) | Optimization through lean production practices | Cleaning rework was eliminated | After implementing JIT, storage time was reduced and protective oil layer on parts is not needed anymore; reduced water consumption since washing was eliminated Reduced glue consumption during manufacturing process |
| Stoll et al. (2008) | Cooling during metal cutting (machinery and workpiece) changed from wet machining to minimum quantity lubrication | Life cycle costs improved by 15% Reduced efforts in handling of contaminated chips | Lower consumption of metalworking fluids (minus 113,500 l p.a.) Reduced water consumption (minus 1.14 m l p.a.) Reduced electrical power consumption (900,000 kWh p.a.) Reduced filter media and disposal, lower compressed air usage Reduced waste water treatment, lower air emissions Higher recycle value for dry chips |
| Takada et al. (2008) | Integration of two or more fabrication processes into a single process by using multi-tone mask technology | Amount and number of material and processes are reduced Cost and time reduction | Less waste produced, less energy consumed |
| Tamosiunas (2014) | Technological upgrades, automating the majority of operations, increasing the level of product heterogeneity, higher level of replication of operations per product category; Employees were trained and re-assigned new tasks or rotated focusing on the customer | Sales increased by 16% | Carbon emissions per m³ of plywood produced decreased by 22% Electrical energy consumed for manufacturing (per m³ of product) reduced by 26% Thermal energy consumed for manufacturing (per m³ of product) reduced by 13% Consumption of motor fuel decreased by 22% |
| Tang et al. (2016) | Algorithm (computerized batching) replaced rule-based (manual) planning approach for batch annealing process | Annual net profit increase of at least USD 1.76 m | Decreased CO2 emissions Reduced consumption of coal, protective gas, electricity and water |
| Tasdemir and Gazo (2019) | Among others benchmarking (KPIs) and root cause analysis lead to - changed material procurement, picking and release - improved facility layout - implementation of 5S and Kanban posts | Financial performance improved from 33% loss to 46% profit Non-value-added time reduced by 89%, value-added-time reduced by 48%, total lead time reduced by 86%, reduced cycle times Labor costs per batch decreased by 42%, material costs decreased by 41%, transportation costs decreased by 40% Reduced defect rate | Reductions in CO2 emissions by 55% Energy consumption reduced by 50% Solid waste generation decreased by 72% Net water footprint did not change |
| Teng et al. (2020) | Structured analysis (incl. waste reduction algorithm) and debottlenecking capacity by changing configurations (T) | Energy consumption is reduced by 93% ROI of 58,36% Payback period of 65 months | Global warming potential reduced by 94% |
| Thanki and Thakkar (2020) | Case 1: Implementation of 5S, Kaizen, TPM DfE | Profit decreased by 68% while costs for raw material decreased by 59% and energy costs decreased by 46% | Solid waste decreased by 69% |
| Case 2: 5S | Profit increased by 30% Costs for raw material increased by 30% and energy costs increased by 22% Lead time decreased by 31% | Waste stayed on same level | |
| Case 3: 5S, TPM | Gross profit decreased by 13% while costs for raw materials decreased by 10%. Energy costs increased by 11% | Solid waste increased by 60% | |
| Cases 4: 5S, Kaizen, SMED, TPM Focus on optimum use of natural resources | Profit increased by 370% while costs for raw material decreased by 37% and energy costs increased by 15% | Solid waste increased by 52% | |
| Case 5: 5S, Kaizen, SMED, TPM, DfE, 3R | Gross profit increased by 18% while costs for raw materials increased by 23% Energy costs decreased by 2% Lead time decreased by 60% Significant improvement of product quality | Waste stayed on same level | |
| Case 6: 5S, Kaizen, SMED, TPM Focus on optimum use of natural resources | Profit decreased by 38% Costs for raw material increased by 11% and energy costs increased by 18% | Solid waste increased by 28% | |
| Case 7: 5S, Kaizen, TPM, 3R | Profit decreased by 10% while costs for raw material decreased by 7% and energy costs increased by 15% | Solid waste increased by 5% | |
| Case 8: 5S, Kaizen, DfE, 3R | Profit increased by 49% while costs for raw material increased by 39% and energy costs decreased by 10% | Solid waste increased by 12% | |
| Tiwari et al. (2020) | Improvement measures (esp. additional equipment and employee training) were identified and implemented through following a framework | 89% cost savings Defect rate decreased by 92% Machine setup time reduced by 80% | CO2 emissions reduced by 95% Scrap reduction of 96% |
| Tokawa et al. (2001) | Application of dry hobbing machines with coolant-free swarf discharge capability | Machining costs reduced by 34% Tool cost reduced by 23% since tool life was extended by five times Labor cost per workpiece reduced by 38% due to doubled cutting speed | Coolant is completely avoided |
| Triebswetter and Hitchens (2005) | Replacement of coal by alternative fuels (e.g. used tires, paper waste) | EUR 125 saved per ton of replaced coal (save energy costs amounting to 7.5% of annual turnover) | One ton of coal is replaced by two tons of alternative fuels |
| save energy costs amounting to 1.7% of annual sales | Use of 17% alternative fuels | ||
| save energy costs amounting to 2.5% of turnover | 20,000 t of tires are used as fuel instead of coal | ||
| Vargas and Scott (2017) | Case 1: Semiautomated process with new technology | 50% less operators needed Process time reduced by 62% | Consumption of natural gas significantly reduced by 11,000m³ p.a |
| Case 2: Floor layout was redesigned to resolve water issues | Improved productivity | Water consumption reduced by 3.3 m l 27,000 l of pit-cleaning waste water p.a. avoided | |
| Case 3: Reuse process and more efficient waste-segregation | Significant reduction of work hours | Avoidance of 90 kg of hazardous waste p.a | |
| Case 4: Development of a distillation process that allowed reuse of hazardous chemicals | Procurement of some chemicals are reduced by 61% | Up to 90% of some chemicals can be reused | |
| Case 5: Extended use of coolant via inverse-osmosis and quality monitoring | Less downtime Reduced product handling | Reduction of 87,500 l of waste coolant p.a | |
| Case 6: Ultrasonic cleaner instead of manual use of solvent-based cleaner | Shorter cycle time | Replacement of 1,000 aerosol cans p.a | |
| Veltri et al. (1999) | Recycling strategy (T) | Cost saving potential of 46% Net present value of recycling is estimated with USD 4.3 m | 70% of ultrapure water can be recycled |
| Vinodh et al. (2016) | Optimized power consumption through machine settings, waste-water treatment, standard operating procedure, 5S activities for two processes, operator workload balancing | Manufacturing costs reduced by 19% Cycle time reduced by 6% Lead time reduced by 52% Value-adding costs reduced by 5% Non-value-adding costs reduced by 38% | CO2 emissions reduced by 20% Consumption of electricity reduced by 30% |
| Wills (2009) | Replacing hazardous solvent by water-based solvent | Savings of USD 6,000 p.a. (payback period of retooling 6 months) | Emission of VOC reduced by 62% |
| Replacing spray paint by powder coating, using different kind of glue | Savings of USD 1m p.a. (payback period of one year) | Significant reduction of emissions (esp. VOC) and waste | |
| Yamazaki (2017) | Integrated and synchronized manufacturing line with downsized equipment | Production costs reduced by 33% Reduced setup time | Energy consumption reduced by 50% Area occupied by equipment reduced by 20% |
| Yang and Feng (2008) | Transformation to circular corporation | Sales increased by 153% Profit increased by 5,521% High investments | Water consumption reduced by 35% COD decreased by 62% SO2 emissions reduced by 59% |
| Yue and You (2013) | Optimization of batch scheduling | Productivity increased by 23% | Environmental impact per unit reduced by 1% |
| Yun et al. (2014) | Cold extrusion is applied to manufacture helical gears | Increased productivity Hardness of gear increased by 37% | Energy consumption reduced by 25% (single-type gear) and 49% (double-type gear) compared to conventional machining CO2 emissions reduced by 40% Material recovery rates increased by 58% (single-type gear) and 91% (double-type gear) |
| Zhang et al. (2018) | Real-time scheduling for remanufacturing of automobile engines via IoT | Manufacturing costs reduced by 34% | Energy consumption reduced by 34% |
| Zhang et al. (2016) | Recovery of industrial waste heat via steam turbine | Payback period of 2.3 years | Burning of 9,853t of standard coal equivalent were avoided |
| Zhi-dong et al. (2011) | Identification and analysis of different options regarding “'cleaner production” (e.g. technological modification, waste treatment and utilization) | Low cost options resulted in benefits of CNY 44.8 m Middle/high cost options added CNY 345m of benefits Expenditure of coal and water per CNY 10k output are reduced by 2.2 and 1.5% respectively | COD reduced by 35% (annual emission reduced by 465 t) Ammonia nitrogen concentrations reduced by 72% (annual emission reduced by 84 t) Phosphorus concentrations reduced by 76% (annual emission reduced by 2.4 t) Solid waste reduced by 3% |
| Zhu et al. (2007) | By-products became additional production lines including a heat and power facility Article is about a corporate group representing six cases | “Quality premium” of 10% for main product Reduced input costs (recovered alkali is half the price of purchased alkali) Reduced production costs | Utilization of by-products from local competitors which would be discarding or incinerating otherwise Reduced pollution (e.g. recovery rate of alkali is 80%) |
| Authors (year) | Description of measures | Economic effects | Ecological effects |
|---|---|---|---|
| Multi-objective optimization using digital process twins and artificial intelligence algorithms | Process queuing time and costs improved by 93% | Total embodied energy reduced by 84% | |
| Optimized, more linear layout to reduce intermediate stocks and movements | Production capacity increased by 13% | Consumption of primary energy per unit reduced by 82% | |
| Collecting and distributing residual CO2 and waste heat from industrial company into greenhouses | User save 50% energy costs | Avoids burning of 55m m³ natural gas p.a. | |
| Implementation of lean principles, esp. Kanban and change of lot size | Lead time and work in process reduced by 83% | Consumption of raw material reduced by 13% | |
| Implementation of cellular manufacturing, continuous flow, supermarket pull system etc. | Production increased by 34% | Electrical energy consumed per product reduced by 45% | |
| Modification of layout and equipment via SMED, audits etc. | Cycle time reduced by 18% | Net power consumption reduced by 25% | |
| Production optimization through motion and time study lead to cycle operation from every third to every fourth shift | Reduced ladle utilization due to reduced number of activities from 66 to 55 | Hydrogen fluoride emissions are reduced by 20.5% | |
| Changes of material (wood type) and machine settings (blade angle, number of saw teeth) | System costs for cutting process decreased by 9% | Material losses reduced by 22% | |
| Improving production via resource leveling, processes integration etc. | Reduced lead time by 63% | CO2 emissions reduced by 77% (net savings of 967t of CO2e per year) | |
| Implementation of a combination of lean and green strategies (e.g. batch size reduction, use of energy-efficient engines) | “Green strategies” contributed 4.7% of the overall 10.8% savings in production costs compared to initial state | ||
| Optimized layout reduces transportation effort and promotes maximum daylight usage | Costs for fuel und electricity decreased by 57% | Fuel consumed in material flow reduced by 62% | |
| Algorithm to rearrange furnace charging | Throughput increased by 7% due to heating time optimization of furnaces | Energy consumption reduced by 10% due to reorganization of the pre-heating furnaces | |
| Modification of equipment (mold, pipeline, ventilation), redesign and automation of cleaning procedure, improved accessory mixing | Processing time reduced by 15% | Material and energy savings, pollution and waste reduction | |
| Optimized chemical composition decreased bleed-off volume without affecting quality and effectiveness of the process | Significant cost savings | Consumption of chemicals reduced by 28% | |
| Optimization of electrostatic powder coat cure oven process | Process time reduced by 5% | Natural gas consumption reduced by 5% | |
| Continuous improvement approach led to the installation of ammonia stripping equipment | Benefit of ammonia recovery of USD 3.4 m p.a | Pollution by ammonia decreased by 65% | |
| In-house additive Manufacturing (T) | Downtime could be reduced by 70–80% compared to conventional manufacturing | Energy consumption could be reduced by 3–5% | |
| Fuzzy rule-based system leads to settings for the cutting parameters to optimize energy consumption, tool life and machining productivity | Increased feed rates reduce energy consumption; this ensures high productivity and reduced CO2 emissions | ||
| Potential of additive manufacturing to industry (T) | Profit might increase by 4% (equivalent to an increase of 15% over the margin with traditional manufacturing and distribution) | Estimated consumption of material reduced by 12% | |
| New coating and laminating process | Increased flexibility | Resin usage reduced by 30% | |
| Casting replaced by powder metallurgy process | Costs per part are three times higher than with casting | Material waste per part reduced by 76% | |
| Combination of cryogenic and minimum quantity lubrication (compared to flood cooling) | Unit production cost of new technology are around 27% lower, but environmental costs are higher | Depending on the use case (esp. cutting speed), the CO2 emissions per part produced are significantly higher | |
| Replacing machines (e.g. from plasma to laser cutting, shot-blasting instead of sand blasting), installation of ventilation and filtering systems | Total production costs reduced by 6% | Cutting process: dust emissions reduced by 50%, material waste reduced by 25% | |
| SMED with focus on CO2 emissions | Idle and setup times reduced by up to 88% | Carbon footprint reduced by up to 81% | |
| Six Sigma extended by environmental variables such as consumption of electricity and chip generation of CNC lathes (T) | Increase the eco-efficiency to about 20% (and reduction of cycle time by 4%) | ||
| Comparison of butane-based and benzene-based maleic anhydride manufacturing technology | Butane process is 34% more profitable | Benzene process consumes less raw material (48%) and water (3%), and generates less wastewater (3%) | |
| Industrial symbiosis where non-marketable products and waste are used by livestock and other enterprises | Investment of EUR 0.4 m | Production waste destined for disposal will become second raw material for processing companies | |
| Optimization of pallet system (T) | Number of pallets and conveyor velocity can be increased | Energy consumption reduced by 61% (for one specific configuration) | |
| Calibration of machines, creation of quick wash program, implementation of new additives and activators | Cost savings of more than 30% | Isopropyl alcohol consumption reduced by 39% | |
| Material flow cost accounting triggered change of manufacturing procedure | profits increased | Material losses of previously 32% was reduced by 80% | |
| Implementation of 5S, VSM and Kaizen | Cost savings for electricity of ZAR 139k p.a | Electricity consumption reduced by 32% | |
| Retrofitting the production lines with specific machines and merging or replacing production steps | Turnover increased by at least 22% due to additional capacities | Generating electricity out of waste | |
| Kaizen approach for improving environmental flows of mass and energy of manufacturing cells | Average cost reduction of 8% on cell level and 4.5% on value stream level | Average resources consumption reduced by 35% | |
| Re-circulating cooling water system with cooling tower and heat-exchanger network interaction (T) | Total cost reduction of 45% compared to conventional system design (300% higher capital costs, but only 31% of operating costs) | 46% of make-up saving, 93% of blow-down water saving | |
| Steam from waste incinerator is used instead of fossil fuel | Cost savings of over USD 4.1 m p.a | CO2 reduction of 45,500 t p.a | |
| Shift from end-of-pipe treatment towards in-process waste reduction | Overall cost savings of USD 1m | Total waste reduced by >50% | |
| Conventional coolants such as air, oils and aqueous emulsions are replaced by cryogenic fluids (esp. liquid nitrogen) | Production costs reduced by up to 70% (depending on cutting speed) | Hazardous oil-based emulsions are avoided | |
| Introduction of a new step in the reduction process that involves recirculation of the pumping water and treating (i.a. screening, flocculation, centrifugation) resultant effluents | Productivity increased by 7% | Reduction of COD by 91.6% | |
| Implementation of measures to reduce VOC emissions (i.a. switching adhesive, recycle solvent) | Savings of CAD 349k p.a. | Reduction of VOC emissions of 35% | |
| Installation of modular gas-based burner technology | Production costs decreased by 48% due to substitution of expensive electricity by cheap gas | Energy demand to melt, transport and hold decreased by 36% | |
| Industrial symbiosis with eight dyadic or triadic relationships exchanging 300,000 t of by-products per year, comprising coal ash, mill scale, electric arc furnace dust, steam, zinc sludge, lead sludge and refractory lining leftover | |||
| Evaluation of an on-site cogeneration system (T) | Expected payback period of 6 years | CO2 emissions avoided in the first year are estimated to be 2,500 t | |
| Implementation of lean principles such as Kaizen, Jidoka and TPM | 33% reduction of cycle time (on average) leading to savings of EUR 124/month of energy costs | Energy consumption reduced by 38% | |
| Optimization through lean production practices | Cleaning rework was eliminated | After implementing JIT, storage time was reduced and protective oil layer on parts is not needed anymore; reduced water consumption since washing was eliminated | |
| Cooling during metal cutting (machinery and workpiece) changed from wet machining to minimum quantity lubrication | Life cycle costs improved by 15% | Lower consumption of metalworking fluids (minus 113,500 l p.a.) | |
| Integration of two or more fabrication processes into a single process by using multi-tone mask technology | Amount and number of material and processes are reduced | Less waste produced, less energy consumed | |
| Technological upgrades, automating the majority of operations, increasing the level of product heterogeneity, higher level of replication of operations per product category; Employees were trained and re-assigned new tasks or rotated focusing on the customer | Sales increased by 16% | Carbon emissions per m³ of plywood produced decreased by 22% | |
| Algorithm (computerized batching) replaced rule-based (manual) planning approach for batch annealing process | Annual net profit increase of at least USD 1.76 m | Decreased CO2 emissions | |
| Among others benchmarking (KPIs) and root cause analysis lead to | Financial performance improved from 33% loss to 46% profit | Reductions in CO2 emissions by 55% | |
| Structured analysis (incl. waste reduction algorithm) and debottlenecking capacity by changing configurations (T) | Energy consumption is reduced by 93% | Global warming potential reduced by 94% | |
| Case 1: Implementation of 5S, Kaizen, TPM | Profit decreased by 68% while costs for raw material decreased by 59% and energy costs decreased by 46% | Solid waste decreased by 69% | |
| Case 2: 5S | Profit increased by 30% | Waste stayed on same level | |
| Case 3: 5S, TPM | Gross profit decreased by 13% while costs for raw materials decreased by 10%. Energy costs increased by 11% | Solid waste increased by 60% | |
| Cases 4: 5S, Kaizen, SMED, TPM | Profit increased by 370% while costs for raw material decreased by 37% and energy costs increased by 15% | Solid waste increased by 52% | |
| Case 5: 5S, Kaizen, SMED, TPM, DfE, 3R | Gross profit increased by 18% while costs for raw materials increased by 23% | Waste stayed on same level | |
| Case 6: 5S, Kaizen, SMED, TPM | Profit decreased by 38% | Solid waste increased by 28% | |
| Case 7: 5S, Kaizen, TPM, 3R | Profit decreased by 10% while | Solid waste increased by 5% | |
| Case 8: 5S, Kaizen, DfE, 3R | Profit increased by 49% while costs for raw material increased by 39% and energy costs decreased by 10% | Solid waste increased by 12% | |
| Improvement measures (esp. additional equipment and employee training) were identified and implemented through following a framework | 89% cost savings | CO2 emissions reduced by 95% | |
| Application of dry hobbing machines with coolant-free swarf discharge capability | Machining costs reduced by 34% | Coolant is completely avoided | |
| Replacement of coal by alternative fuels (e.g. used tires, paper waste) | EUR 125 saved per ton of replaced coal (save energy costs amounting to 7.5% of annual turnover) | One ton of coal is replaced by two tons of alternative fuels | |
| save energy costs amounting to 1.7% of annual sales | Use of 17% alternative fuels | ||
| save energy costs amounting to 2.5% of turnover | 20,000 t of tires are used as fuel instead of coal | ||
| Case 1: Semiautomated process with new technology | 50% less operators needed | Consumption of natural gas significantly reduced by 11,000m³ p.a | |
| Case 2: Floor layout was redesigned to resolve water issues | Improved productivity | Water consumption reduced by 3.3 m l | |
| Case 3: Reuse process and more efficient waste-segregation | Significant reduction of work hours | Avoidance of 90 kg of hazardous waste p.a | |
| Case 4: Development of a distillation process that allowed reuse of hazardous chemicals | Procurement of some chemicals are reduced by 61% | Up to 90% of some chemicals can be reused | |
| Case 5: Extended use of coolant via inverse-osmosis and quality monitoring | Less downtime | Reduction of 87,500 l of waste coolant p.a | |
| Case 6: Ultrasonic cleaner instead of manual use of solvent-based cleaner | Shorter cycle time | Replacement of 1,000 aerosol cans p.a | |
| Recycling strategy (T) | Cost saving potential of 46% | 70% of ultrapure water can be recycled | |
| Optimized power consumption through machine settings, waste-water treatment, standard operating procedure, 5S activities for two processes, operator workload balancing | Manufacturing costs reduced by 19% | CO2 emissions reduced by 20% | |
| Replacing hazardous solvent by water-based solvent | Savings of USD 6,000 p.a. (payback period of retooling 6 months) | Emission of VOC reduced by 62% | |
| Replacing spray paint by powder coating, using different kind of glue | Savings of USD 1m p.a. (payback period of one year) | Significant reduction of emissions (esp. VOC) and waste | |
| Integrated and synchronized manufacturing line with downsized equipment | Production costs reduced by 33% | Energy consumption reduced by 50% | |
| Transformation to circular corporation | Sales increased by 153% | Water consumption reduced by 35% | |
| Optimization of batch scheduling | Productivity increased by 23% | Environmental impact per unit reduced by 1% | |
| Cold extrusion is applied to manufacture helical gears | Increased productivity | Energy consumption reduced by 25% (single-type gear) and 49% (double-type gear) compared to conventional machining | |
| Real-time scheduling for remanufacturing of automobile engines via IoT | Manufacturing costs reduced by 34% | Energy consumption reduced by 34% | |
| Recovery of industrial waste heat via steam turbine | Payback period of 2.3 years | Burning of 9,853t of standard coal equivalent were avoided | |
| Identification and analysis of different options regarding “'cleaner production” (e.g. technological modification, waste treatment and utilization) | Low cost options resulted in benefits of CNY 44.8 m | COD reduced by 35% (annual emission reduced by 465 t) | |
| By-products became additional production lines including a heat and power facility | “Quality premium” of 10% for main product | Utilization of by-products from local competitors which would be discarding or incinerating otherwise | |
Note(s): T: theoretical work; 3R: reduce, reuse, recycle (UNEP, 2004), 5S: workplace organization method; BOD: biochemical oxygen demand; CNC: computer numerical control; CO2e: carbon dioxide equivalent; COD: chemical oxygen demand; GHG: greenhouse gas; JIT: just-in-time production; MTTR: mean time to repair; MTBF: mean time between failure; OEE: overall equipment effectiveness; SMED: single minute exchange of die; TPM: total productive maintenance; VSM: value-stream mapping; VOC: volatile organic compound
Source(s): Authors’ own elaboration
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