Food Sorting Machines Market by Technology (Infrared Sorting, Magnetic Sorting, Metal Detection), Product Type (Bakery & Confectionery, Dairy, Fruits & Vegetables), Automation Level, End User - Global Forecast 2025-2032
Description
The Food Sorting Machines Market was valued at USD 1.23 billion in 2024 and is projected to grow to USD 1.30 billion in 2025, with a CAGR of 5.85%, reaching USD 1.94 billion by 2032.
A comprehensive strategic introduction outlining how technological upgrades, regulatory priorities, and operational constraints shape procurement and deployment decisions for sorting equipment
The food sorting equipment landscape is experiencing accelerated technological and operational change driven by demands for higher throughput, improved contamination control, and enhanced product quality traceability. Over the last several years, manufacturers and processors have increasingly integrated advanced sensory and machine learning controls into sorting lines to reduce waste and to meet stricter food safety standards. Simultaneously, supply chain resilience concerns and rising labor constraints have elevated the value proposition of automation, prompting capital investments in both retrofit solutions and next-generation sorting platforms.
As buyers evaluate equipment strategies, they must balance throughput objectives with sensitivity to small defect detection, material compatibility, and sanitation requirements. This requires careful alignment between product characteristics, production rhythms, and inspection modalities. For procurement teams and operational leaders, the critical first step is to understand how available sensor technologies-optical, infrared, X-ray, magnetic, and metal detection-map to specific product streams and regulatory obligations. Establishing rigorous evaluation criteria and pilot protocols ensures that performance claims translate into measurable improvements on the line, and that integration risks, including downtime and maintenance complexity, are mitigated during roll-out.
How advances in sensing, automation integration, and hygienic design are producing a new generation of connected and precision-focused food sorting systems
Recent years have introduced transformative shifts that reshape adoption curves and supplier strategies across the food sorting domain. Advances in optical sorting algorithms and imaging hardware have dramatically improved defect classification accuracy, enabling differentiation between subtle color, shape, and surface anomalies that previously required manual sorting. Parallel progress in X-ray technologies, including multi-energy capability, has broadened detection envelopes for dense contaminants and internal defects, while infrared sensing provides rapid moisture and compositional differentiation for certain crop and nut applications.
Concurrently, the drive toward automation has matured beyond simple mechanization into systems-level integration that couples sorting machines with line controls, traceability platforms, and predictive maintenance frameworks. This integration has been accelerated by industrial networking standards and by the adoption of edge computing, which reduces latency for real-time decisioning. Another pivotal shift is increased emphasis on hygienic design and washdown-capable materials, responding to heightened sanitation scrutiny. Taken together, these changes create a more connected, precise, and resilient processing environment, prompting buyers to prioritize modularity, software upgradeability, and vendor support ecosystems when selecting equipment.
The cumulative effects of recent tariff changes on procurement strategy, total-cost-of-ownership planning, and regional sourcing decisions across equipment supply chains
Trade policy adjustments and tariff developments can materially affect sourcing strategies, supply chain decisions, and total acquisition costs for sorting equipment and spare parts. Recent tariff actions have introduced complexity into procurement planning by altering landed costs for imported capital equipment and by incentivizing local sourcing where feasible. In response, many manufacturers and major processors have revisited supplier portfolios, increasing engagement with regional system integrators and domestic component manufacturers to reduce exposure to tariff volatility and shipping delays.
Procurement teams are now applying more rigorous total-cost-of-ownership frameworks that account for tariff-driven import surcharges, variable freight conditions, and potential duty classification changes for components such as sensors, conveyors, and control cabinets. These frameworks also consider lead-time variability and the strategic importance of maintaining spare parts inventories to avoid production interruptions. As a result, some buyers are opting for phased deployment plans that prioritize critical lines for onshore supply while maintaining strategic relationships with global OEMs for specialized technologies that are not yet widely produced domestically. Ultimately, tariff dynamics are prompting a dual approach that balances cost control with access to advanced technologies.
Segmentation-driven insights that demonstrate how technology types, product streams, end users, and automation levels jointly determine sorting equipment requirements and procurement trade-offs
Insightful segmentation clarifies how technology choices, product characteristics, end-user profiles, and automation expectations drive divergent solution requirements and procurement priorities. When considering technology, buyers evaluate infrared sorting for compositional and moisture contrasts, magnetic sorting for ferrous contaminant removal, metal detection for fine conductive fragments, optical sorting for surface-based assessments with subcategories that include color-based sorting, defect-oriented inspection, and shape recognition, and X-ray sorting with single-energy options for basic density and foreign-body exclusion and multi-energy configurations for advanced material discrimination. These technology distinctions determine inspection sensitivity, false-reject tendencies, and integration complexity, and should be matched to product vulnerability and desired throughput.
Product-type segmentation further shapes equipment selection and hygiene needs. Bakery and confectionery lines prioritize gentle handling and color fidelity, dairy operations emphasize cleanliness and moisture control, fruits and vegetables demand adaptable handling across fresh, dried, and frozen states, grains and nuts require robust dust mitigation and abrasion-resistant components, while meat and seafood processors focus on contaminant detection and compliance with protein-processing sanitation regimes. End-user segmentation highlights that bakeries, dairy plants, food processors, meat processors, and seafood processors each carry distinct line-speed, traceability, and regulatory priorities that influence preferred equipment footprints and service expectations. Finally, automation-level distinctions between fully automatic, semi-automatic, and manual solutions inform workforce planning, training investments, and maintenance protocols, and they often determine the extent of software and controls integration required for effective deployment.
How regional differences in regulation, supplier networks, and production profiles influence adoption, customization, and service expectations for sorting solutions
Regional dynamics exert a strong influence on technology adoption rates, supplier ecosystems, and regulatory expectations. In the Americas, buyers benefit from a mature supplier base for standard sorting technologies, robust aftermarket support networks, and emphasis on scale-driven throughput solutions that integrate with major processing lines. The region’s focus on rapid time-to-deployment and onshore service capabilities often leads to preferences for modular, retrofit-friendly designs and extended technical support agreements.
Europe, Middle East & Africa present a heterogeneous landscape where stringent food safety regulations, emphasis on sustainability, and diverse production scales create mixed demand profiles. High-consistency processing hubs in Western Europe favor advanced multi-energy X-ray and precision optical solutions, while other markets prioritize cost-effective, hygienically designed equipment that can be adapted to local ingredient profiles. Across the region, sustainability targets and packaging regulations increasingly inform equipment specifications. Asia-Pacific exhibits accelerated adoption of automated sorting driven by labor constraints, rapid capacity expansion in fruits, vegetables, and seafood value chains, and a growing number of domestic suppliers adopting global technology standards. Faster line evolution, cost sensitivity, and a drive for localization shape procurement conversations and supplier partnerships across the region.
Competitive supplier strategies concentrate on sensor differentiation, AI-enabled analytics, and bundled service models to reduce downtime and improve long-term performance
Competitive dynamics among equipment suppliers emphasize product differentiation through sensing capability, software ecosystems, and aftermarket service propositions. Leading vendors are expanding portfolios to include modular sensor packages, AI-enabled defect recognition suites, and subscription-based analytics that support continuous performance tuning. Service models increasingly bundle preventive maintenance, spare part logistics, and remote diagnostics to reduce downtime risk and to offer predictable operational availability.
At the same time, strategic partnerships between technology providers and system integrators are creating end-to-end delivery models that encompass initial line assessment, pilot validation, installation, and post-deployment optimization. OEMs are also investing in training programs and certification pathways for channel partners to ensure consistent installation quality and to protect brand performance. For buyers, vendor selection criteria now weigh not only sensor performance but also the availability of local technical expertise, software update roadmaps, and the ability to support scalable rollouts across multiple facilities. These considerations favor suppliers that can demonstrate reliable field performance, transparent calibration protocols, and robust service-level commitments.
Actionable operator and procurement recommendations to accelerate pilot validation, protect capital investments, and secure service-driven performance across deployments
Industry leaders should adopt a practical sequence of actions to accelerate value realization from sorting investments. First, establish clear outcome metrics tied to quality improvement, yield retention, and contamination prevention so that procurement decisions are measurable and aligned with production KPIs. Next, prioritize pilot programs that replicate peak-line conditions rather than average throughput, thereby validating performance under stress and identifying maintenance or integration pain points before full roll-out.
Procurement teams should also insist on modularity and software upgrade pathways to protect capital investments against obsolescence, and they should negotiate performance-based service agreements that include remote diagnostics and agreed response times for critical spares. Where tariff exposure is material, diversify sourcing to include reliable regional suppliers for standard components while retaining access to specialized global technologies for highly specific detection needs. Finally, invest in workforce upskilling and cross-functional governance that ensures operations, quality, and maintenance teams share ownership of performance metrics and that lessons from pilot deployments are institutionalized across facilities to drive continuous improvement.
A transparent mixed-method research approach built on technical interviews, regulatory review, and comparative technology assessments to ensure reproducible findings
The research methodology combines primary and secondary investigative approaches to ensure robust, traceable findings. Primary research involved structured interviews with equipment end users across bakeries, dairy operations, produce packers, grain and nut handlers, and protein processors, supplemented by technical briefings with engineers and integrators responsible for line design and automation. These engagements focused on real-world performance, downtime causes, integration challenges, and service experiences, providing practical context for technology efficacy and operational constraints.
Secondary research included analysis of regulatory guidance, technical white papers, and vendor technical specifications to corroborate performance claims and to map technology capabilities to product types and sanitation requirements. Comparative technology assessments were conducted to evaluate sensing modalities against criteria such as detection scope, false-reject behavior, hygiene compatibility, and control integration. Where applicable, case studies and pilot outcomes were reviewed to validate typical deployment timelines and to identify common failure modes. The combined approach emphasizes transparency and reproducibility of findings through clearly documented interview frameworks, source catalogs, and assessment rubrics.
Concluding synthesis emphasizing the operational prerequisites, procurement guardrails, and governance steps required to translate sorting technology into sustained production value
The confluence of advanced sensing, software intelligence, and integration-ready architectures is reshaping how food processors manage quality, safety, and throughput. Successful deployments hinge on a clear alignment between product characteristics, selected inspection modalities, and operational objectives. Buyers who prioritize pilot validation under peak conditions, insist on modular upgradeability, and secure robust service frameworks stand to reduce waste, improve product consistency, and lower unplanned downtime risk.
At the same time, tariff volatility and supply chain fragmentation underscore the need for flexible sourcing strategies that balance access to specialized technologies with reliable regional support. Finally, organizations that invest in cross-functional governance, workforce capability building, and data-driven performance monitoring will be better positioned to translate equipment capability into sustained operational improvement. These conclusions provide a practical roadmap for procurement, operations, and engineering teams seeking to modernize inspection capabilities while managing risk and protecting capital.
Note: PDF & Excel + Online Access - 1 Year
A comprehensive strategic introduction outlining how technological upgrades, regulatory priorities, and operational constraints shape procurement and deployment decisions for sorting equipment
The food sorting equipment landscape is experiencing accelerated technological and operational change driven by demands for higher throughput, improved contamination control, and enhanced product quality traceability. Over the last several years, manufacturers and processors have increasingly integrated advanced sensory and machine learning controls into sorting lines to reduce waste and to meet stricter food safety standards. Simultaneously, supply chain resilience concerns and rising labor constraints have elevated the value proposition of automation, prompting capital investments in both retrofit solutions and next-generation sorting platforms.
As buyers evaluate equipment strategies, they must balance throughput objectives with sensitivity to small defect detection, material compatibility, and sanitation requirements. This requires careful alignment between product characteristics, production rhythms, and inspection modalities. For procurement teams and operational leaders, the critical first step is to understand how available sensor technologies-optical, infrared, X-ray, magnetic, and metal detection-map to specific product streams and regulatory obligations. Establishing rigorous evaluation criteria and pilot protocols ensures that performance claims translate into measurable improvements on the line, and that integration risks, including downtime and maintenance complexity, are mitigated during roll-out.
How advances in sensing, automation integration, and hygienic design are producing a new generation of connected and precision-focused food sorting systems
Recent years have introduced transformative shifts that reshape adoption curves and supplier strategies across the food sorting domain. Advances in optical sorting algorithms and imaging hardware have dramatically improved defect classification accuracy, enabling differentiation between subtle color, shape, and surface anomalies that previously required manual sorting. Parallel progress in X-ray technologies, including multi-energy capability, has broadened detection envelopes for dense contaminants and internal defects, while infrared sensing provides rapid moisture and compositional differentiation for certain crop and nut applications.
Concurrently, the drive toward automation has matured beyond simple mechanization into systems-level integration that couples sorting machines with line controls, traceability platforms, and predictive maintenance frameworks. This integration has been accelerated by industrial networking standards and by the adoption of edge computing, which reduces latency for real-time decisioning. Another pivotal shift is increased emphasis on hygienic design and washdown-capable materials, responding to heightened sanitation scrutiny. Taken together, these changes create a more connected, precise, and resilient processing environment, prompting buyers to prioritize modularity, software upgradeability, and vendor support ecosystems when selecting equipment.
The cumulative effects of recent tariff changes on procurement strategy, total-cost-of-ownership planning, and regional sourcing decisions across equipment supply chains
Trade policy adjustments and tariff developments can materially affect sourcing strategies, supply chain decisions, and total acquisition costs for sorting equipment and spare parts. Recent tariff actions have introduced complexity into procurement planning by altering landed costs for imported capital equipment and by incentivizing local sourcing where feasible. In response, many manufacturers and major processors have revisited supplier portfolios, increasing engagement with regional system integrators and domestic component manufacturers to reduce exposure to tariff volatility and shipping delays.
Procurement teams are now applying more rigorous total-cost-of-ownership frameworks that account for tariff-driven import surcharges, variable freight conditions, and potential duty classification changes for components such as sensors, conveyors, and control cabinets. These frameworks also consider lead-time variability and the strategic importance of maintaining spare parts inventories to avoid production interruptions. As a result, some buyers are opting for phased deployment plans that prioritize critical lines for onshore supply while maintaining strategic relationships with global OEMs for specialized technologies that are not yet widely produced domestically. Ultimately, tariff dynamics are prompting a dual approach that balances cost control with access to advanced technologies.
Segmentation-driven insights that demonstrate how technology types, product streams, end users, and automation levels jointly determine sorting equipment requirements and procurement trade-offs
Insightful segmentation clarifies how technology choices, product characteristics, end-user profiles, and automation expectations drive divergent solution requirements and procurement priorities. When considering technology, buyers evaluate infrared sorting for compositional and moisture contrasts, magnetic sorting for ferrous contaminant removal, metal detection for fine conductive fragments, optical sorting for surface-based assessments with subcategories that include color-based sorting, defect-oriented inspection, and shape recognition, and X-ray sorting with single-energy options for basic density and foreign-body exclusion and multi-energy configurations for advanced material discrimination. These technology distinctions determine inspection sensitivity, false-reject tendencies, and integration complexity, and should be matched to product vulnerability and desired throughput.
Product-type segmentation further shapes equipment selection and hygiene needs. Bakery and confectionery lines prioritize gentle handling and color fidelity, dairy operations emphasize cleanliness and moisture control, fruits and vegetables demand adaptable handling across fresh, dried, and frozen states, grains and nuts require robust dust mitigation and abrasion-resistant components, while meat and seafood processors focus on contaminant detection and compliance with protein-processing sanitation regimes. End-user segmentation highlights that bakeries, dairy plants, food processors, meat processors, and seafood processors each carry distinct line-speed, traceability, and regulatory priorities that influence preferred equipment footprints and service expectations. Finally, automation-level distinctions between fully automatic, semi-automatic, and manual solutions inform workforce planning, training investments, and maintenance protocols, and they often determine the extent of software and controls integration required for effective deployment.
How regional differences in regulation, supplier networks, and production profiles influence adoption, customization, and service expectations for sorting solutions
Regional dynamics exert a strong influence on technology adoption rates, supplier ecosystems, and regulatory expectations. In the Americas, buyers benefit from a mature supplier base for standard sorting technologies, robust aftermarket support networks, and emphasis on scale-driven throughput solutions that integrate with major processing lines. The region’s focus on rapid time-to-deployment and onshore service capabilities often leads to preferences for modular, retrofit-friendly designs and extended technical support agreements.
Europe, Middle East & Africa present a heterogeneous landscape where stringent food safety regulations, emphasis on sustainability, and diverse production scales create mixed demand profiles. High-consistency processing hubs in Western Europe favor advanced multi-energy X-ray and precision optical solutions, while other markets prioritize cost-effective, hygienically designed equipment that can be adapted to local ingredient profiles. Across the region, sustainability targets and packaging regulations increasingly inform equipment specifications. Asia-Pacific exhibits accelerated adoption of automated sorting driven by labor constraints, rapid capacity expansion in fruits, vegetables, and seafood value chains, and a growing number of domestic suppliers adopting global technology standards. Faster line evolution, cost sensitivity, and a drive for localization shape procurement conversations and supplier partnerships across the region.
Competitive supplier strategies concentrate on sensor differentiation, AI-enabled analytics, and bundled service models to reduce downtime and improve long-term performance
Competitive dynamics among equipment suppliers emphasize product differentiation through sensing capability, software ecosystems, and aftermarket service propositions. Leading vendors are expanding portfolios to include modular sensor packages, AI-enabled defect recognition suites, and subscription-based analytics that support continuous performance tuning. Service models increasingly bundle preventive maintenance, spare part logistics, and remote diagnostics to reduce downtime risk and to offer predictable operational availability.
At the same time, strategic partnerships between technology providers and system integrators are creating end-to-end delivery models that encompass initial line assessment, pilot validation, installation, and post-deployment optimization. OEMs are also investing in training programs and certification pathways for channel partners to ensure consistent installation quality and to protect brand performance. For buyers, vendor selection criteria now weigh not only sensor performance but also the availability of local technical expertise, software update roadmaps, and the ability to support scalable rollouts across multiple facilities. These considerations favor suppliers that can demonstrate reliable field performance, transparent calibration protocols, and robust service-level commitments.
Actionable operator and procurement recommendations to accelerate pilot validation, protect capital investments, and secure service-driven performance across deployments
Industry leaders should adopt a practical sequence of actions to accelerate value realization from sorting investments. First, establish clear outcome metrics tied to quality improvement, yield retention, and contamination prevention so that procurement decisions are measurable and aligned with production KPIs. Next, prioritize pilot programs that replicate peak-line conditions rather than average throughput, thereby validating performance under stress and identifying maintenance or integration pain points before full roll-out.
Procurement teams should also insist on modularity and software upgrade pathways to protect capital investments against obsolescence, and they should negotiate performance-based service agreements that include remote diagnostics and agreed response times for critical spares. Where tariff exposure is material, diversify sourcing to include reliable regional suppliers for standard components while retaining access to specialized global technologies for highly specific detection needs. Finally, invest in workforce upskilling and cross-functional governance that ensures operations, quality, and maintenance teams share ownership of performance metrics and that lessons from pilot deployments are institutionalized across facilities to drive continuous improvement.
A transparent mixed-method research approach built on technical interviews, regulatory review, and comparative technology assessments to ensure reproducible findings
The research methodology combines primary and secondary investigative approaches to ensure robust, traceable findings. Primary research involved structured interviews with equipment end users across bakeries, dairy operations, produce packers, grain and nut handlers, and protein processors, supplemented by technical briefings with engineers and integrators responsible for line design and automation. These engagements focused on real-world performance, downtime causes, integration challenges, and service experiences, providing practical context for technology efficacy and operational constraints.
Secondary research included analysis of regulatory guidance, technical white papers, and vendor technical specifications to corroborate performance claims and to map technology capabilities to product types and sanitation requirements. Comparative technology assessments were conducted to evaluate sensing modalities against criteria such as detection scope, false-reject behavior, hygiene compatibility, and control integration. Where applicable, case studies and pilot outcomes were reviewed to validate typical deployment timelines and to identify common failure modes. The combined approach emphasizes transparency and reproducibility of findings through clearly documented interview frameworks, source catalogs, and assessment rubrics.
Concluding synthesis emphasizing the operational prerequisites, procurement guardrails, and governance steps required to translate sorting technology into sustained production value
The confluence of advanced sensing, software intelligence, and integration-ready architectures is reshaping how food processors manage quality, safety, and throughput. Successful deployments hinge on a clear alignment between product characteristics, selected inspection modalities, and operational objectives. Buyers who prioritize pilot validation under peak conditions, insist on modular upgradeability, and secure robust service frameworks stand to reduce waste, improve product consistency, and lower unplanned downtime risk.
At the same time, tariff volatility and supply chain fragmentation underscore the need for flexible sourcing strategies that balance access to specialized technologies with reliable regional support. Finally, organizations that invest in cross-functional governance, workforce capability building, and data-driven performance monitoring will be better positioned to translate equipment capability into sustained operational improvement. These conclusions provide a practical roadmap for procurement, operations, and engineering teams seeking to modernize inspection capabilities while managing risk and protecting capital.
Note: PDF & Excel + Online Access - 1 Year
Table of Contents
187 Pages
- 1. Preface
- 1.1. Objectives of the Study
- 1.2. Market Segmentation & Coverage
- 1.3. Years Considered for the Study
- 1.4. Currency
- 1.5. Language
- 1.6. Stakeholders
- 2. Research Methodology
- 3. Executive Summary
- 4. Market Overview
- 5. Market Insights
- 5.1. Integration of AI-driven machine vision and deep learning algorithms for precise defect and size grading
- 5.2. Deployment of compact modular sorting machines tailored for small-scale and urban farming operations
- 5.3. Implementation of hyperspectral and multispectral cameras for non-invasive quality and ripeness assessment
- 5.4. Adoption of IoT-enabled sensors and cloud analytics for predictive maintenance and uptime optimization
- 5.5. Development of eco-friendly materials and energy-efficient designs to reduce operational carbon footprint
- 5.6. Integration of robotic arms and collaborative robots for high-speed sorting and reduced manual labor requirements
- 5.7. Customization of sorting parameters and modular software interfaces to accommodate diverse produce varieties
- 5.8. Advancements in washdown and hygienic design standards for food safety compliance and sanitation efficiency
- 5.9. Utilization of real-time data dashboards and KPIs for continuous quality control and yield optimization
- 5.10. Emergence of handheld optical sorting devices with smartphone connectivity for field quality assessment
- 6. Cumulative Impact of United States Tariffs 2025
- 7. Cumulative Impact of Artificial Intelligence 2025
- 8. Food Sorting Machines Market, by Technology
- 8.1. Infrared Sorting
- 8.2. Magnetic Sorting
- 8.3. Metal Detection
- 8.4. Optical Sorting
- 8.4.1. Color Sorting
- 8.4.2. Defect Sorting
- 8.4.3. Shape Sorting
- 8.5. X-Ray Sorting
- 8.5.1. Multi-Energy
- 8.5.2. Single-Energy
- 9. Food Sorting Machines Market, by Product Type
- 9.1. Bakery & Confectionery
- 9.2. Dairy
- 9.3. Fruits & Vegetables
- 9.3.1. Dried
- 9.3.2. Fresh
- 9.3.3. Frozen
- 9.4. Grains & Nuts
- 9.5. Meat
- 9.6. Seafood
- 10. Food Sorting Machines Market, by Automation Level
- 10.1. Fully Automatic
- 10.2. Manual
- 10.3. Semi-Automatic
- 11. Food Sorting Machines Market, by End User
- 11.1. Bakeries
- 11.2. Dairy Plants
- 11.3. Food Processors
- 11.4. Meat Processors
- 11.5. Seafood Processors
- 12. Food Sorting Machines Market, by Region
- 12.1. Americas
- 12.1.1. North America
- 12.1.2. Latin America
- 12.2. Europe, Middle East & Africa
- 12.2.1. Europe
- 12.2.2. Middle East
- 12.2.3. Africa
- 12.3. Asia-Pacific
- 13. Food Sorting Machines Market, by Group
- 13.1. ASEAN
- 13.2. GCC
- 13.3. European Union
- 13.4. BRICS
- 13.5. G7
- 13.6. NATO
- 14. Food Sorting Machines Market, by Country
- 14.1. United States
- 14.2. Canada
- 14.3. Mexico
- 14.4. Brazil
- 14.5. United Kingdom
- 14.6. Germany
- 14.7. France
- 14.8. Russia
- 14.9. Italy
- 14.10. Spain
- 14.11. China
- 14.12. India
- 14.13. Japan
- 14.14. Australia
- 14.15. South Korea
- 15. Competitive Landscape
- 15.1. Market Share Analysis, 2024
- 15.2. FPNV Positioning Matrix, 2024
- 15.3. Competitive Analysis
- 15.3.1. Bühler Group
- 15.3.2. TOMRA Systems ASA
- 15.3.3. Satake Corporation
- 15.3.4. Binder+Co AG
- 15.3.5. Cimbria A/S
- 15.3.6. Hefei Taihe Optoelectronic Technology Co., Ltd.
- 15.3.7. Aweta GmbH
- 15.3.8. Compac Sorting Equipment Ltd.
- 15.3.9. Raytec Vision S.p.A.
- 15.3.10. Elbicon NV
- 15.3.11. Greefa Machinebouw B.V.
- 15.3.12. Meyer GmbH
- 15.3.13. Newtec Group A/S
- 15.3.14. Odenberg Engineering GmbH
- 15.3.15. Pellenc S.A.
- 15.3.16. BoMill AB
- 15.3.17. Conceptronic S.A.S.
- 15.3.18. Food Machinery Australia Pty Ltd.
- 15.3.19. InLine Vision Systems
- 15.3.20. LOMA Systems
- 15.3.21. Sesotec GmbH
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